TensorFlow | 06A6390F3269A6045F8C101444C9E9949CD23DE0

TensorFlow

Name	_TensorFlow	DOWNLOAD Copy Link
Total Size	6.7 GB
Total Files	1275
Last Seen	2025-02-17 23:59
Hash	06A6390F3269A6045F8C101444C9E9949CD23DE0

/Pluralsight Path. Building Machine Learning Solutions with TensorFlow (2019)/
scr.png	192.4 KB
~i.txt	1.1 KB
/.../A1. TensorFlow. Getting Started (Jerry Kurata, 2017)/
exercise.7z	20.7 MB
playlist.m3u	2.5 KB
~i.txt	1.7 KB
/.../A1. TensorFlow. Getting Started (Jerry Kurata, 2017)/1. Course Overview/
1. Course Overview.mp4	3.8 MB
1. Course Overview.vtt	2.3 KB
/.../A1. TensorFlow. Getting Started (Jerry Kurata, 2017)/2. Introduction/
1. Introduction.mp4	5.4 MB
1. Introduction.vtt	4.2 KB
2. TensorFlow as Interface and Implementation.mp4	5.9 MB
2. TensorFlow as Interface and Implementation.vtt	5.2 KB
3. Why Is It Called TensorFlow.mp4	3.9 MB
3. Why Is It Called TensorFlow.vtt	3.5 KB
4. Skills and Course Structure.mp4	8.2 MB
4. Skills and Course Structure.vtt	8.1 KB
/.../A1. TensorFlow. Getting Started (Jerry Kurata, 2017)/3. Introducing TensorFlow/
1. Introduction.mp4	1.2 MB
1. Introduction.vtt	1.6 KB
2. Installing TensorFlow.mp4	32.0 MB
2. Installing TensorFlow.vtt	11.0 KB
3. Getting Hands-on.mp4	6.3 MB
3. Getting Hands-on.vtt	4.0 KB
4. Building Our First Model.mp4	2.7 MB
4. Building Our First Model.vtt	2.7 KB
5. TensorFlow Training.mp4	27.0 MB
5. TensorFlow Training.vtt	13.6 KB
6. Tensor Properties.mp4	5.1 MB
6. Tensor Properties.vtt	5.6 KB
7. Gradient Descent.mp4	6.4 MB
7. Gradient Descent.vtt	2.7 KB
8. Gradient Descent in Action.mp4	7.2 MB
8. Gradient Descent in Action.vtt	2.7 KB
9. Summary.mp4	1.0 MB
9. Summary.vtt	1.6 KB
/.../4. Creating Neural Networks in TensorFlow/
1. Introduction.mp4	2.7 MB
1. Introduction.vtt	3.3 KB
2. Introduction to Neural Networks.mp4	5.5 MB
2. Introduction to Neural Networks.vtt	5.1 KB
3. Neural Network Symbology and Terminology.mp4	3.0 MB
3. Neural Network Symbology and Terminology.vtt	2.1 KB
4. Simple MNIST.mp4	23.4 MB
4. Simple MNIST.vtt	14.2 KB
5. Deep MNIST.mp4	8.4 MB
5. Deep MNIST.vtt	8.6 KB
6. Coding Deep MNIST.mp4	23.3 MB
6. Coding Deep MNIST.vtt	12.4 KB
7. Summary.mp4	3.5 MB
7. Summary.vtt	2.7 KB
/.../5. Debugging and Monitoring/
1. Introduction.mp4	1.5 MB
1. Introduction.vtt	1.8 KB
2. Why Is TensorFlow Different.mp4	4.1 MB
2. Why Is TensorFlow Different.vtt	4.3 KB
3. Using Names and Name Scope.mp4	18.1 MB
3. Using Names and Name Scope.vtt	5.7 KB
4. Introducing TensorBoard.mp4	3.3 MB
4. Introducing TensorBoard.vtt	3.5 KB
5. Using TensorBoard - Part 1.mp4	16.4 MB
5. Using TensorBoard - Part 1.vtt	7.5 KB
6. Using TensorBoard - Part 2.mp4	19.4 MB
6. Using TensorBoard - Part 2.vtt	8.4 KB
7. Summary.mp4	2.5 MB
7. Summary.vtt	2.9 KB
/.../6. Transfer Learning with TensorFlow/
1. Introduction.mp4	5.5 MB
1. Introduction.vtt	1.3 KB
2. The Need for Transfer Learning.mp4	3.6 MB
2. The Need for Transfer Learning.vtt	3.8 KB
3. Transfer Learning Basics.mp4	4.0 MB
3. Transfer Learning Basics.vtt	4.2 KB
4. Implementing Transfer Learning in TensorFlow.mp4	31.3 MB
4. Implementing Transfer Learning in TensorFlow.vtt	12.2 KB
5. Retraining Inception.mp4	12.7 MB
5. Retraining Inception.vtt	4.4 KB
6. Using Our Retrained Model.mp4	14.7 MB
6. Using Our Retrained Model.vtt	4.0 KB
7. Summary.mp4	2.2 MB
7. Summary.vtt	2.8 KB
/.../7. Extending TensorFlow with Add-ons/
1. Introduction.mp4	6.2 MB
1. Introduction.vtt	2.1 KB
2. Keras.mp4	2.1 MB
2. Keras.vtt	2.8 KB
3. Using Keras.mp4	22.1 MB
3. Using Keras.vtt	10.3 KB
4. DeepMNIST in Keras.mp4	18.5 MB
4. DeepMNIST in Keras.vtt	7.8 KB
5. TFLearn.mp4	2.0 MB
5. TFLearn.vtt	2.5 KB
6. Using TFLearn.mp4	14.2 MB
6. Using TFLearn.vtt	4.0 KB
7. DeepMNIST in TFLearn.mp4	14.4 MB
7. DeepMNIST in TFLearn.vtt	5.3 KB
8. Summary.mp4	5.2 MB
8. Summary.vtt	3.2 KB
/.../A1. TensorFlow. Getting Started (Jerry Kurata, 2017)/8. Summary/
1. Last Words.mp4	4.7 MB
1. Last Words.vtt	6.3 KB
/.../A2. Understanding the Foundations of TensorFlow (Janani Ravi, 2017)/
exercise.7z	1.7 MB
playlist.m3u	2.4 KB
~i.txt	1.6 KB
/.../A2. Understanding the Foundations of TensorFlow (Janani Ravi, 2017)/1. Course Overview/
1. Course Overview.mp4	4.0 MB
1. Course Overview.vtt	2.7 KB
/.../A2. Understanding the Foundations of TensorFlow (Janani Ravi, 2017)/2. Introducing TensorFlow/
1. Version Check.mp4	736.4 KB
1. Version Check.vtt	0.0 KB
2. Prerequisites and Course Overview.mp4	6.0 MB
2. Prerequisites and Course Overview.vtt	5.5 KB
3. Traditional ML Algorithms.mp4	11.8 MB
3. Traditional ML Algorithms.vtt	12.5 KB
4. Representation ML Algorithms.mp4	3.9 MB
4. Representation ML Algorithms.vtt	3.4 KB
5. Deep Learning and Neural Networks.mp4	8.1 MB
5. Deep Learning and Neural Networks.vtt	6.6 KB
6. Introducing TensorFlow.mp4	6.8 MB
6. Introducing TensorFlow.vtt	6.8 KB
7. The World as a Graph.mp4	4.9 MB
7. The World as a Graph.vtt	4.3 KB
8. Downloading and Installing TensorFlow.mp4	22.9 MB
8. Downloading and Installing TensorFlow.vtt	12.8 KB
/.../3. Introducing Computation Graphs/
1. The Computation Graph.mp4	6.6 MB
1. The Computation Graph.vtt	5.4 KB
2. Modeling Cyclic Dependencies.mp4	4.9 MB
2. Modeling Cyclic Dependencies.vtt	4.2 KB
3. Building, Running, and Visualizing Graphs.mp4	15.0 MB
3. Building, Running, and Visualizing Graphs.vtt	11.6 KB
4. Computation Graphs and Distributed Systems.mp4	3.7 MB
4. Computation Graphs and Distributed Systems.vtt	2.8 KB
5. Simple Math Operations.mp4	14.2 MB
5. Simple Math Operations.vtt	8.7 KB
6. Tensors.mp4	5.9 MB
6. Tensors.vtt	6.2 KB
7. Rank of a Tensor.mp4	1.8 MB
7. Rank of a Tensor.vtt	1.8 KB
8. Tensor Math.mp4	7.2 MB
8. Tensor Math.vtt	5.1 KB
9. Numpy and TensorFlow.mp4	4.7 MB
9. Numpy and TensorFlow.vtt	3.8 KB
/.../4. Digging Deeper into Fundamentals/
1. A TensorFlow Example - Linear Regression.mp4	9.5 MB
1. A TensorFlow Example - Linear Regression.vtt	9.3 KB
2. Linear Regression in Practice.mp4	3.9 MB
2. Linear Regression in Practice.vtt	4.1 KB
3. Placeholders.mp4	10.8 MB
3. Placeholders.vtt	8.1 KB
4. Fetches and the Feed Dictionary.mp4	13.9 MB
4. Fetches and the Feed Dictionary.vtt	7.4 KB
5. Variables.mp4	18.6 MB
5. Variables.vtt	11.6 KB
6. Default and Explicitly Specified Graphs.mp4	6.3 MB
6. Default and Explicitly Specified Graphs.vtt	4.7 KB
7. Named Scopes.mp4	10.0 MB
7. Named Scopes.vtt	6.0 KB
8. Interactive Sessions.mp4	3.0 MB
8. Interactive Sessions.vtt	2.7 KB
9. Quick Overview - Linear Regression in TensorFlow.mp4	8.1 MB
9. Quick Overview - Linear Regression in TensorFlow.vtt	6.1 KB
/.../5. Working with Images/
1. Image Recognition and Neural Networks.mp4	6.7 MB
1. Image Recognition and Neural Networks.vtt	4.5 KB
2. Representing Images as Tensors.mp4	5.0 MB
2. Representing Images as Tensors.vtt	5.2 KB
3. Transposing Images.mp4	14.0 MB
3. Transposing Images.vtt	7.7 KB
4. Resizing Images.mp4	19.9 MB
4. Resizing Images.vtt	9.6 KB
5. Representing a List of Images as a 4D Tensor.mp4	21.2 MB
5. Representing a List of Images as a 4D Tensor.vtt	8.8 KB
/.../6. Solving Basic Math Functions/
1. The MNIST Dataset.mp4	7.7 MB
1. The MNIST Dataset.vtt	4.5 KB
2. The K-nearest-neighbors Algorithm.mp4	11.3 MB
2. The K-nearest-neighbors Algorithm.vtt	9.4 KB
3. L1 Distance.mp4	3.1 MB
3. L1 Distance.vtt	4.0 KB
4. KNN in TensorFlow.mp4	10.7 MB
4. KNN in TensorFlow.vtt	8.3 KB
5. Calculating L1 in TensorFlow.mp4	8.3 MB
5. Calculating L1 in TensorFlow.vtt	5.7 KB
6. Measuring Accuracy.mp4	6.7 MB
6. Measuring Accuracy.vtt	3.8 KB
/.../A3. Building Regression Models Using TensorFlow (Vitthal Srinivasan, 2017)/
exercise.7z	1.9 MB
playlist.m3u	2.7 KB
~i.txt	1.7 KB
/.../A3. Building Regression Models Using TensorFlow (Vitthal Srinivasan, 2017)/1. Course Overview/
1. Course Overview.mp4	3.3 MB
1. Course Overview.vtt	2.1 KB
/.../2. Learning Using Neurons/
01. Version Check.txt	0.0 KB
02. Understanding Deep Learning.mp4	6.7 MB
02. Understanding Deep Learning.vtt	7.9 KB
03. Deep Learning as a Representation Learning System.mp4	8.5 MB
03. Deep Learning as a Representation Learning System.vtt	7.7 KB
04. Neurons as Learning Units.mp4	8.1 MB
04. Neurons as Learning Units.vtt	6.5 KB
05. Understanding a Neuron.mp4	12.4 MB
05. Understanding a Neuron.vtt	11.6 KB
06. Activation Functions.mp4	3.9 MB
06. Activation Functions.vtt	3.6 KB
07. Regression - The Simplest Neural Network.mp4	7.8 MB
07. Regression - The Simplest Neural Network.vtt	7.5 KB
08. XOR - A Slightly More Complex Neural Network.mp4	11.9 MB
08. XOR - A Slightly More Complex Neural Network.vtt	11.1 KB
09. Learning XOR.mp4	8.9 MB
09. Learning XOR.vtt	7.6 KB
10. Choice of Activation Function.mp4	4.5 MB
10. Choice of Activation Function.vtt	3.8 KB
11. Prequisites and Course Outline.mp4	2.2 MB
11. Prequisites and Course Outline.vtt	2.2 KB
/.../3. Building Linear Regression Models Using TensorFlow/
1. Outlining Your Approach.mp4	10.2 MB
1. Outlining Your Approach.vtt	6.0 KB
2. A Baseline Implementation.mp4	15.0 MB
2. A Baseline Implementation.vtt	11.1 KB
3. Understanding Gradient Descent.mp4	15.6 MB
3. Understanding Gradient Descent.vtt	15.2 KB
4. Implementing Stochastic Gradient Descent in TensorFlow.mp4	22.6 MB
4. Implementing Stochastic Gradient Descent in TensorFlow.vtt	15.4 KB
5. Instrumenting and Using TensorBoard.mp4	11.9 MB
5. Instrumenting and Using TensorBoard.vtt	7.6 KB
6. Implementing Batch Gradient Descent in TensorFlow.mp4	14.7 MB
6. Implementing Batch Gradient Descent in TensorFlow.vtt	9.5 KB
7. Implementing Multiple Regression.mp4	12.2 MB
7. Implementing Multiple Regression.vtt	8.8 KB
/.../4. Building Logistic Regression Models Using TensorFlow/
1. The Intuition Behind Logistic Regression.mp4	9.9 MB
1. The Intuition Behind Logistic Regression.vtt	10.1 KB
2. Logistic Regression and Linear Regression.mp4	5.7 MB
2. Logistic Regression and Linear Regression.vtt	6.7 KB
3. A Baseline Implementation.mp4	11.6 MB
3. A Baseline Implementation.vtt	7.2 KB
4. Logistic Regression in TensorFlow.mp4	9.3 MB
4. Logistic Regression in TensorFlow.vtt	9.5 KB
5. The Implications of Using Softmax Activation.mp4	10.5 MB
5. The Implications of Using Softmax Activation.vtt	10.4 KB
6. Cross Entropy.mp4	3.2 MB
6. Cross Entropy.vtt	3.3 KB
7. Implementing Linear Classification in TensorFlow.mp4	16.9 MB
7. Implementing Linear Classification in TensorFlow.vtt	10.0 KB
8. Calculating Accuracy.mp4	12.1 MB
8. Calculating Accuracy.vtt	8.8 KB
/.../5. Building Generalized Linear Models Using Estimators/
1. How Estimators Work.mp4	19.5 MB
1. How Estimators Work.vtt	11.8 KB
2. Linear Regression with Estimators.mp4	10.0 MB
2. Linear Regression with Estimators.vtt	3.8 KB
3. Logistic Regression with Estimators.mp4	10.7 MB
3. Logistic Regression with Estimators.vtt	4.2 KB
4. Extending Estimators with Custom Models.mp4	20.7 MB
4. Extending Estimators with Custom Models.vtt	10.3 KB
5. Course Summary.mp4	3.6 MB
5. Course Summary.vtt	3.2 KB
/.../A4. Building Classification Models with TensorFlow (Janani Ravi, 2017)/
exercise.7z	197.0 MB
playlist.m3u	4.0 KB
~i.txt	1.6 KB
/.../A4. Building Classification Models with TensorFlow (Janani Ravi, 2017)/1. Course Overview/
1. Course Overview.mp4	4.2 MB
1. Course Overview.vtt	2.6 KB
/.../2. Overview of Classification Models/
1. Version Check.mp4	736.4 KB
1. Version Check.vtt	0.0 KB
2. Prerequisites and Software Needed for This Course.mp4	5.6 MB
2. Prerequisites and Software Needed for This Course.vtt	5.6 KB
3. Classification and Classifiers.mp4	7.9 MB
3. Classification and Classifiers.vtt	8.1 KB
4. Using Accuracy to Evaluate Models.mp4	6.1 MB
4. Using Accuracy to Evaluate Models.vtt	6.3 KB
5. Using Precision and Recall to Evaluate Models.mp4	2.7 MB
5. Using Precision and Recall to Evaluate Models.vtt	2.6 KB
6. The PrecisionRecall Tradeoff.mp4	7.0 MB
6. The PrecisionRecall Tradeoff.vtt	6.9 KB
7. The Precision-Recall Tradeoff.mp4	5.1 MB
7. The Precision-Recall Tradeoff.vtt	5.5 KB
8. Binary, Multilabel, Multiclass, and Multioutput Classifiers.mp4	7.5 MB
8. Binary, Multilabel, Multiclass, and Multioutput Classifiers.vtt	6.1 KB
/.../3. Simple Classification Models in TensorFlow/
01. Representing Images as Tensors.mp4	6.7 MB
01. Representing Images as Tensors.vtt	6.2 KB
02. The K-nearest Neighbors Algorithm.mp4	5.2 MB
02. The K-nearest Neighbors Algorithm.vtt	4.4 KB
03. Distance Measures.mp4	2.7 MB
03. Distance Measures.vtt	2.7 KB
04. Demo - Environment and Package Setup.mp4	5.0 MB
04. Demo - Environment and Package Setup.vtt	2.9 KB
05. Demo - Image Classification Using K-nearest Neighbors.mp4	24.1 MB
05. Demo - Image Classification Using K-nearest Neighbors.vtt	14.5 KB
06. The Intuition Behind Logistic Regression.mp4	7.6 MB
06. The Intuition Behind Logistic Regression.vtt	8.0 KB
07. Logistic Regression for Prediction.mp4	3.4 MB
07. Logistic Regression for Prediction.vtt	3.0 KB
08. Cross-entropy as a Cost Function.mp4	3.1 MB
08. Cross-entropy as a Cost Function.vtt	3.6 KB
09. Demo - Exploring the Census Dataset.mp4	9.0 MB
09. Demo - Exploring the Census Dataset.vtt	5.5 KB
10. Feature Engineering with Bucketized and Crossed Columns.mp4	5.2 MB
10. Feature Engineering with Bucketized and Crossed Columns.vtt	4.9 KB
11. Working with Estimators in TensorFlow.mp4	6.8 MB
11. Working with Estimators in TensorFlow.vtt	6.3 KB
12. Demo - Income Prediction Using Logistic Regression.mp4	18.2 MB
12. Demo - Income Prediction Using Logistic Regression.vtt	10.2 KB
/.../4. Convolutional Neural Networks for Classification in TensorFlow/
01. Neurons and Neural Networks.mp4	12.9 MB
01. Neurons and Neural Networks.vtt	9.0 KB
02. Understanding How Convolution Works.mp4	11.0 MB
02. Understanding How Convolution Works.vtt	8.7 KB
03. Zero Padding and Stride Size.mp4	7.4 MB
03. Zero Padding and Stride Size.vtt	6.1 KB
04. Introducing Convolutional Neural Networks.mp4	4.8 MB
04. Introducing Convolutional Neural Networks.vtt	4.6 KB
05. Convolutional Layers and Feature Maps.mp4	12.0 MB
05. Convolutional Layers and Feature Maps.vtt	8.7 KB
06. Pooling Layers.mp4	7.5 MB
06. Pooling Layers.vtt	5.1 KB
07. Architecture of CNNs.mp4	11.0 MB
07. Architecture of CNNs.vtt	8.0 KB
08. Demo - Image Classification Using CNNs (MNIST Dataset).mp4	23.6 MB
08. Demo - Image Classification Using CNNs (MNIST Dataset).vtt	14.7 KB
09. Demo - Exploring the CIFAR-10 Dataset.mp4	10.5 MB
09. Demo - Exploring the CIFAR-10 Dataset.vtt	6.5 KB
10. Demo - Image Classification Using CNNs (CIFAR-10 Dataset).mp4	19.3 MB
10. Demo - Image Classification Using CNNs (CIFAR-10 Dataset).vtt	10.9 KB
/.../5. Recurrent Neural Networks for Classification in TensorFlow/
01. Why Is the Past Important.mp4	6.7 MB
01. Why Is the Past Important.vtt	6.0 KB
02. Understaning the Recurrent Neuron.mp4	6.2 MB
02. Understaning the Recurrent Neuron.vtt	6.4 KB
03. Training Using Back Propogation.mp4	8.7 MB
03. Training Using Back Propogation.vtt	7.5 KB
04. Demo - Classifying Images Using RNNs (MNIST Dataset).mp4	6.6 MB
04. Demo - Classifying Images Using RNNs (MNIST Dataset).vtt	6.1 KB
05. Dealing with Vanishing and Exploding Gradients.mp4	12.9 MB
05. Dealing with Vanishing and Exploding Gradients.vtt	8.9 KB
06. The LSTM Memory Cell.mp4	8.0 MB
06. The LSTM Memory Cell.vtt	7.9 KB
07. Word Vector Encodings.mp4	11.5 MB
07. Word Vector Encodings.vtt	11.1 KB
08. Demo - Exploring the DBPedia Dataset for Text Classification.mp4	16.6 MB
08. Demo - Exploring the DBPedia Dataset for Text Classification.vtt	9.7 KB
09. Demo - Text Classification Using RNNs.mp4	22.0 MB
09. Demo - Text Classification Using RNNs.vtt	11.5 KB
10. Summary and Next Steps for Learning.mp4	2.3 MB
10. Summary and Next Steps for Learning.vtt	2.0 KB
/.../A5. Building Unsupervised Learning Models with TensorFlow (Janani Ravi, 2017)/
exercise.7z	3.3 MB
playlist.m3u	3.4 KB
~i.txt	1.5 KB
/.../A5. Building Unsupervised Learning Models with TensorFlow (Janani Ravi, 2017)/1. Course Overview/
1. Course Overview.mp4	4.4 MB
1. Course Overview.vtt	2.6 KB
/.../2. Introduction to Unsupervised Learning/
1. Version Check.mp4	744.6 KB
1. Version Check.vtt	0.0 KB
2. Prerequisites and Required Software.mp4	5.1 MB
2. Prerequisites and Required Software.vtt	5.5 KB
3. Supervised Learning.mp4	8.3 MB
3. Supervised Learning.vtt	8.8 KB
4. Unsupervised Learning.mp4	10.5 MB
4. Unsupervised Learning.vtt	8.1 KB
5. Introduction to Clustering.mp4	4.4 MB
5. Introduction to Clustering.vtt	4.9 KB
6. Minimize Intra-cluster Similarity; Maximize Inter-cluster Similarity.mp4	5.5 MB
6. Minimize Intra-cluster Similarity; Maximize Inter-cluster Similarity.vtt	3.2 KB
7. The Intuition Behind How Autoencoders Work.mp4	3.4 MB
7. The Intuition Behind How Autoencoders Work.vtt	3.5 KB
8. Understanding Principal Components Analysis.mp4	9.8 MB
8. Understanding Principal Components Analysis.vtt	10.4 KB
9. Dimensionality Reducing Using Autoencoders.mp4	9.5 MB
9. Dimensionality Reducing Using Autoencoders.vtt	8.6 KB
/.../3. Clustering Using Unsupervised Learning/
01. The Intuition Behind K-means Clustering.mp4	9.6 MB
01. The Intuition Behind K-means Clustering.vtt	7.8 KB
02. Setting up for K-means Clustering Demos.mp4	4.8 MB
02. Setting up for K-means Clustering Demos.vtt	3.0 KB
03. Demo - K-means Clustering on 1D Arrays.mp4	21.4 MB
03. Demo - K-means Clustering on 1D Arrays.vtt	10.8 KB
04. K-means Clustering - Algorithm and Design Choices.mp4	9.3 MB
04. K-means Clustering - Algorithm and Design Choices.vtt	7.8 KB
05. Demo - K-means Clustering on 2D Arrays.mp4	19.7 MB
05. Demo - K-means Clustering on 2D Arrays.vtt	9.7 KB
06. Hyperparameter Tuning.mp4	7.5 MB
06. Hyperparameter Tuning.vtt	8.4 KB
07. Demo - K-means Clustering on the MNIST Dataset.mp4	16.0 MB
07. Demo - K-means Clustering on the MNIST Dataset.vtt	9.0 KB
08. Demo - Tweaking the Algorithm on the MNIST Dataset.mp4	13.3 MB
08. Demo - Tweaking the Algorithm on the MNIST Dataset.vtt	7.3 KB
09. Understanding Hierarchical Clustering.mp4	9.1 MB
09. Understanding Hierarchical Clustering.vtt	7.9 KB
10. Use Cases of Clustering.mp4	4.1 MB
10. Use Cases of Clustering.vtt	3.4 KB
/.../4. Understanding Neurons and Neural Networks/
1. Deep Learning, Neural Networks, and Neurons.mp4	12.4 MB
1. Deep Learning, Neural Networks, and Neurons.vtt	8.8 KB
2. How Does a Neuron Work.mp4	13.4 MB
2. How Does a Neuron Work.vtt	10.5 KB
3. Gradient Descent Optimization.mp4	6.4 MB
3. Gradient Descent Optimization.vtt	5.5 KB
4. Back Propagation in a Neural Network.mp4	3.5 MB
4. Back Propagation in a Neural Network.vtt	2.5 KB
5. Vanishing, Exploding Gradients, and Dying Neurons.mp4	10.1 MB
5. Vanishing, Exploding Gradients, and Dying Neurons.vtt	9.2 KB
6. Overfitting, Dropout, and Regularisation.mp4	8.3 MB
6. Overfitting, Dropout, and Regularisation.vtt	8.1 KB
7. Overfitting, Regularisation, and Dropout.mp4	10.8 MB
7. Overfitting, Regularisation, and Dropout.vtt	8.3 KB
/.../5. Autoencoders Using Unsupervised Learning/
01. Autoencoders as an Unsupervised Learning Technique.mp4	3.5 MB
01. Autoencoders as an Unsupervised Learning Technique.vtt	2.9 KB
02. Autoencoders Learn the Input to Reproduce at the Output.mp4	4.4 MB
02. Autoencoders Learn the Input to Reproduce at the Output.vtt	4.4 KB
03. Principal Components Analysis.mp4	6.1 MB
03. Principal Components Analysis.vtt	5.5 KB
04. Demo - Implementing PCA Using Matplotlib.mp4	17.6 MB
04. Demo - Implementing PCA Using Matplotlib.vtt	10.1 KB
05. The Undercomplete Autoencoder.mp4	10.9 MB
05. The Undercomplete Autoencoder.vtt	8.8 KB
06. Demo - Implementing an Autoencoder to Perform PCA.mp4	20.3 MB
06. Demo - Implementing an Autoencoder to Perform PCA.vtt	10.8 KB
07. Demo - Implementing the Stacked Autoencoder.mp4	25.4 MB
07. Demo - Implementing the Stacked Autoencoder.vtt	15.6 KB
08. Demo - Implementing a Stacked Autoencoder with Dropout.mp4	9.1 MB
08. Demo - Implementing a Stacked Autoencoder with Dropout.vtt	5.2 KB
09. Demo - Implementing a Denoising Autoencoder.mp4	4.8 MB
09. Demo - Implementing a Denoising Autoencoder.vtt	4.2 KB
10. Denoising Autoencoders and Unsupervised Pre-training.mp4	7.5 MB
10. Denoising Autoencoders and Unsupervised Pre-training.vtt	4.3 KB
11. Use Cases of Autoencoders.mp4	7.0 MB
11. Use Cases of Autoencoders.vtt	5.3 KB
/.../B1. Debugging and Monitoring TensorFlow Programs (Janani Ravi, 2018)/
exercise.7z	456.7 KB
playlist.m3u	2.6 KB
~i.txt	2.3 KB
/.../B1. Debugging and Monitoring TensorFlow Programs (Janani Ravi, 2018)/1. Course Overview/
1. Course Overview.mp4	4.3 MB
1. Course Overview.vtt	2.8 KB
/.../2. Introducing TensorFlow Debugging Methods/
01. Version Check.mp4	738.6 KB
01. Version Check.vtt	0.0 KB
02. Module Overview.mp4	3.4 MB
02. Module Overview.vtt	2.6 KB
03. Prerequisites and Course Overview.mp4	3.8 MB
03. Prerequisites and Course Overview.vtt	4.4 KB
04. A Brief Overview of Computation Graphs.mp4	3.8 MB
04. A Brief Overview of Computation Graphs.vtt	3.0 KB
05. Debugging TensorFlow Programs.mp4	4.8 MB
05. Debugging TensorFlow Programs.vtt	5.5 KB
06. Fetching Tensors - Computing Intermediate Values.mp4	8.3 MB
06. Fetching Tensors - Computing Intermediate Values.vtt	6.0 KB
07. Fetching Tensors - A Neural Network Example.mp4	12.5 MB
07. Fetching Tensors - A Neural Network Example.vtt	6.3 KB
08. Fetching Tensors - Side Effects.mp4	10.3 MB
08. Fetching Tensors - Side Effects.vtt	4.5 KB
09. Partial Runs.mp4	11.4 MB
09. Partial Runs.vtt	7.8 KB
10. Introducing tf.Print().mp4	8.7 MB
10. Introducing tf.Print().vtt	6.8 KB
11. tf.Print() - A Neural Network Example.mp4	18.2 MB
11. tf.Print() - A Neural Network Example.vtt	5.6 KB
12. Introducing tf.Assert().mp4	21.9 MB
12. Introducing tf.Assert().vtt	10.6 KB
13. Traditional Python Debuggers.mp4	15.9 MB
13. Traditional Python Debuggers.vtt	5.3 KB
14. Interposing Python Code in Computation Graphs.mp4	16.2 MB
14. Interposing Python Code in Computation Graphs.vtt	5.8 KB
15. Introducing tfdbg and TensorBoard.mp4	3.4 MB
15. Introducing tfdbg and TensorBoard.vtt	2.8 KB
/.../3. Applying tfdbg to Common Use-cases/
1. Module Overview.mp4	2.2 MB
1. Module Overview.vtt	1.9 KB
2. The Curses Library for tfdbg.mp4	9.2 MB
2. The Curses Library for tfdbg.vtt	5.2 KB
3. Introducing tfdbg Commands.mp4	18.4 MB
3. Introducing tfdbg Commands.vtt	13.0 KB
4. Debugging Shortcuts and Multiple Session Runs.mp4	20.3 MB
4. Debugging Shortcuts and Multiple Session Runs.vtt	10.5 KB
5. Using has_inf_or_nan and Custom Filters.mp4	19.5 MB
5. Using has_inf_or_nan and Custom Filters.vtt	11.1 KB
6. Using Filters with Neural Networks.mp4	22.5 MB
6. Using Filters with Neural Networks.vtt	10.5 KB
7. Debugging Estimators and Experiments.mp4	11.5 MB
7. Debugging Estimators and Experiments.vtt	7.2 KB
8. Debugging Keras Models.mp4	8.9 MB
8. Debugging Keras Models.vtt	6.5 KB
/.../4. Visualizing TensorFlow Using TensorBoard/
01. Module Overview.mp4	2.1 MB
01. Module Overview.vtt	1.9 KB
02. Introducing TensorBoard.mp4	8.0 MB
02. Introducing TensorBoard.vtt	6.6 KB
03. Naming Tensors and Nodes.mp4	8.6 MB
03. Naming Tensors and Nodes.vtt	6.3 KB
04. Using Named Scopes.mp4	15.3 MB
04. Using Named Scopes.vtt	8.1 KB
05. Scalar Summaries.mp4	21.9 MB
05. Scalar Summaries.vtt	9.8 KB
06. Histograms.mp4	5.2 MB
06. Histograms.vtt	5.7 KB
07. Moving Mean Normal Distribution.mp4	7.0 MB
07. Moving Mean Normal Distribution.vtt	4.9 KB
08. More Histograms.mp4	6.4 MB
08. More Histograms.vtt	3.9 KB
09. Runtime Statistics.mp4	8.3 MB
09. Runtime Statistics.vtt	4.1 KB
10. Working with Images.mp4	11.9 MB
10. Working with Images.vtt	8.1 KB
/.../B2. Deploying TensorFlow Models to AWS, Azure, and the GCP (Janani Ravi, 2018)/
exercise.7z	1.8 MB
playlist.m3u	4.4 KB
~i.txt	1.8 KB
/.../B2. Deploying TensorFlow Models to AWS, Azure, and the GCP (Janani Ravi, 2018)/1. Course Overview/
1. Course Overview.mp4	4.8 MB
1. Course Overview.vtt	3.0 KB
/.../2. Using TensorFlow Serving/
01. Module Overview.mp4	2.5 MB
01. Module Overview.vtt	2.0 KB
02. Prerequisites and Course Overview.mp4	4.0 MB
02. Prerequisites and Course Overview.vtt	4.1 KB
03. The Machine Learning Workflow - Local Serving.mp4	4.5 MB
03. The Machine Learning Workflow - Local Serving.vtt	4.4 KB
04. Demo - Exploring the Churn Prediction Dataset.mp4	9.2 MB
04. Demo - Exploring the Churn Prediction Dataset.vtt	5.4 KB
05. Demo - Training and the Experiment Function.mp4	9.4 MB
05. Demo - Training and the Experiment Function.vtt	4.9 KB
06. The Saved Model.mp4	2.9 MB
06. The Saved Model.vtt	3.1 KB
07. The TensorFlow Model Server.mp4	2.4 MB
07. The TensorFlow Model Server.vtt	2.1 KB
08. gRPC and Protocol Buffers.mp4	3.8 MB
08. gRPC and Protocol Buffers.vtt	2.7 KB
09. Demo - Setting up the Azure VM.mp4	7.7 MB
09. Demo - Setting up the Azure VM.vtt	4.4 KB
10. Demo - Installing TensorFlow, gRPC, Serving APIs and the Model Server.mp4	8.9 MB
10. Demo - Installing TensorFlow, gRPC, Serving APIs and the Model Server.vtt	4.4 KB
11. Demo - Deploying and Hosting the MNIST Classification Model.mp4	10.0 MB
11. Demo - Deploying and Hosting the MNIST Classification Model.vtt	4.9 KB
12. Demo - Setting up the Churn Model.mp4	8.1 MB
12. Demo - Setting up the Churn Model.vtt	4.4 KB
13. Demo - Training and Saving the Model.mp4	12.2 MB
13. Demo - Training and Saving the Model.vtt	5.8 KB
14. Demo - Making Predictions from a Saved Model.mp4	17.3 MB
14. Demo - Making Predictions from a Saved Model.vtt	8.5 KB
/.../3. Containerizing TensorFlow Models Using Docker on Microsoft Azure/
1. Module Overview.mp4	2.5 MB
1. Module Overview.vtt	2.0 KB
2. Azure ML IaaS and PaaS Options.mp4	8.8 MB
2. Azure ML IaaS and PaaS Options.vtt	8.5 KB
3. Containers and VMs.mp4	5.5 MB
3. Containers and VMs.vtt	4.4 KB
4. Demo - Docker CE Install.mp4	6.3 MB
4. Demo - Docker CE Install.vtt	3.6 KB
5. Demo - Building the Docker Image.mp4	11.1 MB
5. Demo - Building the Docker Image.vtt	5.4 KB
6. Demo - Running a Docker Container for Predictions.mp4	4.5 MB
6. Demo - Running a Docker Container for Predictions.vtt	3.0 KB
7. Demo - Registering the Image with Docker Hub.mp4	7.2 MB
7. Demo - Registering the Image with Docker Hub.vtt	4.0 KB
8. Demo - Running Docker Using the Docker Hub Image.mp4	6.2 MB
8. Demo - Running Docker Using the Docker Hub Image.vtt	3.2 KB
9. Demo - Making Predictions from a Saved Model Using a Dock.mp4	6.7 MB
9. Demo - Making Predictions from a Saved Model Using a Dock.vtt	4.0 KB
/.../4. Deploying TensorFlow Models on Amazon AWS/
01. Module Overview.mp4	1.6 MB
01. Module Overview.vtt	1.3 KB
02. The Machine Learning Workflow - SageMaker.mp4	5.9 MB
02. The Machine Learning Workflow - SageMaker.vtt	5.9 KB
03. Training the Model.mp4	3.2 MB
03. Training the Model.vtt	2.7 KB
04. Deploying the Model.mp4	4.7 MB
04. Deploying the Model.vtt	3.9 KB
05. Training and Inference Code Interface.mp4	2.7 MB
05. Training and Inference Code Interface.vtt	2.7 KB
06. Demo - Setting up an S3 Bucket.mp4	5.2 MB
06. Demo - Setting up an S3 Bucket.vtt	2.6 KB
07. Demo - Setting up a Notebook Instance.mp4	5.6 MB
07. Demo - Setting up a Notebook Instance.vtt	3.1 KB
08. Demo - Data Preparation.mp4	6.4 MB
08. Demo - Data Preparation.vtt	3.6 KB
09. Demo - Setting up the TensorFlow Model.mp4	7.7 MB
09. Demo - Setting up the TensorFlow Model.vtt	3.6 KB
10. Demo - Training and Deploying the Model.mp4	9.1 MB
10. Demo - Training and Deploying the Model.vtt	3.8 KB
11. Demo - Models and Endpoints.mp4	5.8 MB
11. Demo - Models and Endpoints.vtt	3.2 KB
/.../5. Deploying TensorFlow Models on the Google Cloud Platform/
01. Module Overview.mp4	2.5 MB
01. Module Overview.vtt	2.1 KB
02. Cloud ML Engine vs. SageMaker.mp4	7.4 MB
02. Cloud ML Engine vs. SageMaker.vtt	5.4 KB
03. The Machine Learning Workflow - Cloud ML Engine.mp4	7.2 MB
03. The Machine Learning Workflow - Cloud ML Engine.vtt	5.8 KB
04. Training the Model.mp4	6.8 MB
04. Training the Model.vtt	5.6 KB
05. Deploying the Model.mp4	2.3 MB
05. Deploying the Model.vtt	2.2 KB
06. Demo - Connecting to Datalab.mp4	10.2 MB
06. Demo - Connecting to Datalab.vtt	4.9 KB
07. Demo - Creating a GCS Bucket.mp4	3.4 MB
07. Demo - Creating a GCS Bucket.vtt	1.5 KB
08. Demo - Data Preparation.mp4	6.8 MB
08. Demo - Data Preparation.vtt	3.3 KB
09. Demo - Setting up Bucket Permissions.mp4	10.3 MB
09. Demo - Setting up Bucket Permissions.vtt	4.3 KB
10. Demo - Python Package Contents.mp4	11.3 MB
10. Demo - Python Package Contents.vtt	6.1 KB
11. Demo - Local Training and Prediction.mp4	7.1 MB
11. Demo - Local Training and Prediction.vtt	2.9 KB
12. Demo - Distributed Training and Deployment.mp4	10.8 MB
12. Demo - Distributed Training and Deployment.vtt	4.6 KB
13. Demo - Making Predictions Using Cloud ML Endpoints.mp4	4.8 MB
13. Demo - Making Predictions Using Cloud ML Endpoints.vtt	2.2 KB
14. Summary and Further Study.mp4	2.6 MB
14. Summary and Further Study.vtt	2.5 KB
/.../C1. Language Modeling with Recurrent Neural Networks in TensorFlow (Janani Ravi, 2018)/
exercise.7z	3.3 MB
playlist.m3u	3.9 KB
~i.txt	1.9 KB
/.../C1. Language Modeling with Recurrent Neural Networks in TensorFlow (Janani Ravi, 2018)/1. Course Overview/
1. Course Overview.mp4	3.9 MB
1. Course Overview.vtt	2.7 KB
/.../2. Applying Bidirectional Recurrent Neural Networks to Word Recognition/
01. Version Check.mp4	753.9 KB
01. Version Check.vtt	0.0 KB
02. Module Overview.mp4	3.2 MB
02. Module Overview.vtt	2.7 KB
03. Prerequisites and Course Outline.mp4	3.4 MB
03. Prerequisites and Course Outline.vtt	3.6 KB
04. The Recurrent Neuron.mp4	5.1 MB
04. The Recurrent Neuron.vtt	5.5 KB
05. Training a Recurrent Neural Network.mp4	8.6 MB
05. Training a Recurrent Neural Network.vtt	7.9 KB
06. The Long Memory Cell.mp4	7.2 MB
06. The Long Memory Cell.vtt	7.3 KB
07. Bidirectional RNNs.mp4	11.8 MB
07. Bidirectional RNNs.vtt	10.9 KB
08. OCR - A Sequence Labelling Problem.mp4	5.2 MB
08. OCR - A Sequence Labelling Problem.vtt	5.1 KB
09. OCR File Format.mp4	5.6 MB
09. OCR File Format.vtt	5.9 KB
10. Features and Labels for OCR.mp4	2.4 MB
10. Features and Labels for OCR.vtt	3.1 KB
11. Conventional RNN Architecture.mp4	8.5 MB
11. Conventional RNN Architecture.vtt	7.6 KB
12. Bidirectional RNN Architecture.mp4	5.4 MB
12. Bidirectional RNN Architecture.vtt	4.4 KB
/.../3. Implementing Character Recognition Using Bidirectional RNNs/
01. Module Overview.mp4	2.0 MB
01. Module Overview.vtt	2.0 KB
02. Running Jupyter Notebook and Import Statements.mp4	4.7 MB
02. Running Jupyter Notebook and Import Statements.vtt	4.5 KB
03. Download and Parse OCR File.mp4	4.7 MB
03. Download and Parse OCR File.vtt	3.5 KB
04. Features and Labels.mp4	14.4 MB
04. Features and Labels.vtt	10.4 KB
05. Shuffle and Feed in Training Data.mp4	6.0 MB
05. Shuffle and Feed in Training Data.vtt	5.0 KB
06. Sequence Length Calculations.mp4	3.7 MB
06. Sequence Length Calculations.vtt	3.0 KB
07. Building the RNN.mp4	13.6 MB
07. Building the RNN.vtt	10.4 KB
08. Training and Evaluating the RNN.mp4	11.7 MB
08. Training and Evaluating the RNN.vtt	9.3 KB
09. Manually Setup the Bidirectional RNN.mp4	18.2 MB
09. Manually Setup the Bidirectional RNN.vtt	9.0 KB
10. Bidirectional RNN Using the TF Library.mp4	6.9 MB
10. Bidirectional RNN Using the TF Library.vtt	3.9 KB
/.../4. Applying RNNs to Character Prediction for Text Generation/
1. Module Overview.mp4	2.8 MB
1. Module Overview.vtt	2.4 KB
2. Using Neural Networks for Natural Language Processing.mp4	7.2 MB
2. Using Neural Networks for Natural Language Processing.vtt	6.8 KB
3. Language Modeling Problems.mp4	6.3 MB
3. Language Modeling Problems.vtt	7.0 KB
4. The Multi-RNN Cell.mp4	9.2 MB
4. The Multi-RNN Cell.vtt	8.1 KB
5. Generate Training Data and Labels Using a Sliding Window.mp4	8.8 MB
5. Generate Training Data and Labels Using a Sliding Window.vtt	6.7 KB
6. Text Generation Using Character Prediction.mp4	2.0 MB
6. Text Generation Using Character Prediction.vtt	2.2 KB
7. RNN Architecture for Text Prediction.mp4	9.9 MB
7. RNN Architecture for Text Prediction.vtt	8.5 KB
8. Understanding Perplexity.mp4	9.0 MB
8. Understanding Perplexity.vtt	8.6 KB
/.../5. Implementing RNNs for Character Prediction Used to Generate Text/
1. Module Overview.mp4	1.8 MB
1. Module Overview.vtt	1.5 KB
2. Character Prediction - Retrieve Data from ArXiv.o.mp4	17.3 MB
2. Character Prediction - Retrieve Data from ArXiv.o.vtt	8.6 KB
3. Representing Characters in One Hot Encoding.mp4	8.9 MB
3. Representing Characters in One Hot Encoding.vtt	5.7 KB
4. Training the Model.mp4	17.0 MB
4. Training the Model.vtt	10.6 KB
5. Build the RNN for Prediction.mp4	8.8 MB
5. Build the RNN for Prediction.vtt	4.8 KB
6. Text Generation Using Character Prediction.mp4	21.7 MB
6. Text Generation Using Character Prediction.vtt	13.0 KB
7. Summary and Further Reading.mp4	2.1 MB
7. Summary and Further Reading.vtt	2.1 KB
/.../C2. Implementing Image Recognition Systems with TensorFlow (Jon Flanders, 2019)/
exercise.7z	553.6 MB
playlist.m3u	1.5 KB
~i.txt	1.7 KB
/.../C2. Implementing Image Recognition Systems with TensorFlow (Jon Flanders, 2019)/1. Course Overview/
1. Course Overview.mp4	2.6 MB
1. Course Overview.vtt	1.8 KB
/.../C2. Implementing Image Recognition Systems with TensorFlow (Jon Flanders, 2019)/2. Introduction/
1. Introduction.mp4	4.5 MB
1. Introduction.vtt	4.6 KB
2. Some ML Imaging Basics.mp4	6.5 MB
2. Some ML Imaging Basics.vtt	5.2 KB
3. ML and Imaging.mp4	8.3 MB
3. ML and Imaging.vtt	6.0 KB
4. Over and Underfitting.mp4	3.0 MB
4. Over and Underfitting.vtt	2.9 KB
5. Summary.mp4	258.4 KB
5. Summary.vtt	0.3 KB
/.../3. Picking and Using a Model/
1. Introduction.mp4	2.7 MB
1. Introduction.vtt	2.5 KB
2. Steps for Picking a Model.mp4	2.6 MB
2. Steps for Picking a Model.vtt	2.4 KB
3. Picking Your Model.mp4	1.2 MB
3. Picking Your Model.vtt	1.2 KB
4. Demo - Using a TensorFlow Model.mp4	11.5 MB
4. Demo - Using a TensorFlow Model.vtt	4.4 KB
5. Demo - Creating a Session and Using Tensorboard.mp4	15.1 MB
5. Demo - Creating a Session and Using Tensorboard.vtt	5.4 KB
6. Demo - Getting Predictions.mp4	9.4 MB
6. Demo - Getting Predictions.vtt	2.2 KB
7. Demo - Predictions into Human Readable Names.mp4	35.8 MB
7. Demo - Predictions into Human Readable Names.vtt	8.1 KB
/.../C2. Implementing Image Recognition Systems with TensorFlow (Jon Flanders, 2019)/4. Transfer Learning/
1. Introduction.mp4	7.1 MB
1. Introduction.vtt	7.5 KB
2. Transfer Learning Limitations.mp4	2.1 MB
2. Transfer Learning Limitations.vtt	1.2 KB
3. Demo - Transfer Learning.mp4	11.1 MB
3. Demo - Transfer Learning.vtt	3.0 KB
4. Demo - Preparing the Images.mp4	28.9 MB
4. Demo - Preparing the Images.vtt	9.9 KB
5. Demo - TensorFlow Hub and Retraining.mp4	31.3 MB
5. Demo - TensorFlow Hub and Retraining.vtt	9.7 KB
6. Demo - Code Updates to Run the New Model.mp4	31.0 MB
6. Demo - Code Updates to Run the New Model.vtt	9.6 KB
7. Summary.mp4	659.4 KB
7. Summary.vtt	0.5 KB
/.../5. Localization and Segmentation/
1. Introduction.mp4	3.9 MB
1. Introduction.vtt	2.7 KB
2. Localization.mp4	5.0 MB
2. Localization.vtt	3.4 KB
3. Segementation.mp4	35.0 MB
3. Segementation.vtt	11.5 KB
4. Demo - Segmentation.mp4	31.8 MB
4. Demo - Segmentation.vtt	9.0 KB
5. Summary.mp4	611.3 KB
5. Summary.vtt	0.5 KB
/.../C2. Implementing Image Recognition Systems with TensorFlow (Jon Flanders, 2019)/6. Face Recognition/
1. Introduction.mp4	2.3 MB
1. Introduction.vtt	1.9 KB
2. Demo - Using Facenet.mp4	23.6 MB
2. Demo - Using Facenet.vtt	7.3 KB
3. Demo - Building the Classifier.mp4	20.6 MB
3. Demo - Building the Classifier.vtt	6.5 KB
4. Summary.mp4	613.6 KB
4. Summary.vtt	0.4 KB
/.../C3. Implementing Predictive Analytics with TensorFlow (Justin Flett, 2018)/
exercise.7z	2.5 MB
playlist.m3u	1.5 KB
~i.txt	1.5 KB
/.../C3. Implementing Predictive Analytics with TensorFlow (Justin Flett, 2018)/1. Course Overview/
1. Course Overview.mp4	4.3 MB
1. Course Overview.vtt	2.3 KB
/.../2. Implementing Supervised Learning Systems/
1. Introduction.mp4	1.1 MB
1. Introduction.vtt	0.9 KB
2. Understanding Supervised Learning and Linear Regression.mp4	6.3 MB
2. Understanding Supervised Learning and Linear Regression.vtt	4.5 KB
3. Implementing Linear Regression.mp4	42.7 MB
3. Implementing Linear Regression.vtt	16.8 KB
4. Understanding Neural Networks.mp4	3.7 MB
4. Understanding Neural Networks.vtt	3.6 KB
5. Implementing Neural Networks.mp4	17.4 MB
5. Implementing Neural Networks.vtt	6.3 KB
6. Summary.mp4	1.4 MB
6. Summary.vtt	1.3 KB
/.../3. Implementing Recommendation Systems/
1. Introduction.mp4	1.9 MB
1. Introduction.vtt	1.4 KB
2. Understanding Recommendation Learning Systems.mp4	8.3 MB
2. Understanding Recommendation Learning Systems.vtt	6.5 KB
3. Understanding Matrix Factorization.mp4	4.9 MB
3. Understanding Matrix Factorization.vtt	4.7 KB
4. Implementing a Small-scale Collaborative Filtering System.mp4	24.7 MB
4. Implementing a Small-scale Collaborative Filtering System.vtt	11.1 KB
5. Implementing a Larger-scale Collaborative Filtering System.mp4	14.0 MB
5. Implementing a Larger-scale Collaborative Filtering System.vtt	5.4 KB
6. Summary.mp4	3.3 MB
6. Summary.vtt	2.8 KB
/.../4. Implementing Reinforcement Learning Systems/
1. Introduction.mp4	1.4 MB
1. Introduction.vtt	1.1 KB
2. Understanding Reinforcement Learning Systems.mp4	7.5 MB
2. Understanding Reinforcement Learning Systems.vtt	6.6 KB
3. Implementing a Simple Reinforcement Learning System.mp4	25.6 MB
3. Implementing a Simple Reinforcement Learning System.vtt	13.1 KB
4. Understanding Markov Decision Process and Policy-based Agents.mp4	5.4 MB
4. Understanding Markov Decision Process and Policy-based Agents.vtt	4.8 KB
5. Further Learning and Next Steps.mp4	3.7 MB
5. Further Learning and Next Steps.vtt	3.6 KB
6. Summary.mp4	2.9 MB
6. Summary.vtt	2.5 KB
/.../C4. Sentiment Analysis with Recurrent Neural Networks in TensorFlow (Janani Ravi, 2017)/
exercise.7z	137.6 MB
playlist.m3u	3.3 KB
~i.txt	1.9 KB
/.../C4. Sentiment Analysis with Recurrent Neural Networks in TensorFlow (Janani Ravi, 2017)/1. Course Overview/
1. Course Overview.mp4	3.6 MB
1. Course Overview.vtt	2.4 KB
/.../2. Applying Word Vector Embeddings to Language Modeling/
1. Version Check.mp4	741.9 KB
1. Version Check.vtt	0.0 KB
2. Classification as a Machine Learning Problem.mp4	4.7 MB
2. Classification as a Machine Learning Problem.vtt	4.5 KB
3. Prerequisites and Software.mp4	3.5 MB
3. Prerequisites and Software.vtt	3.6 KB
4. A Rule-based System for Sentiment Analysis.mp4	7.5 MB
4. A Rule-based System for Sentiment Analysis.vtt	7.4 KB
5. An Introduction to Neural Networks.mp4	11.0 MB
5. An Introduction to Neural Networks.vtt	8.9 KB
6. One-hot Encoding.mp4	7.4 MB
6. One-hot Encoding.vtt	6.6 KB
7. Frequency-based Embeddings.mp4	12.6 MB
7. Frequency-based Embeddings.vtt	12.2 KB
8. Prediction-based Embeddings.mp4	7.9 MB
8. Prediction-based Embeddings.vtt	7.4 KB
9. Introducing Word2Vec.mp4	5.5 MB
9. Introducing Word2Vec.vtt	5.2 KB
/.../3. Implementing Word Embeddings in TensorFlow/
01. Overview.mp4	2.7 MB
01. Overview.vtt	2.3 KB
02. Maximum Likelihood Estimation.mp4	7.1 MB
02. Maximum Likelihood Estimation.vtt	7.3 KB
03. The Continuous Bag of Words Neural Network.mp4	8.4 MB
03. The Continuous Bag of Words Neural Network.vtt	8.0 KB
04. The Skip-gram Neural Network.mp4	2.2 MB
04. The Skip-gram Neural Network.vtt	1.8 KB
05. Useful Python Packages.mp4	6.2 MB
05. Useful Python Packages.vtt	2.5 KB
06. Demo - Download Data and Extract Words.mp4	9.5 MB
06. Demo - Download Data and Extract Words.vtt	7.6 KB
07. Demo - Build and Prepare Dataset.mp4	8.6 MB
07. Demo - Build and Prepare Dataset.vtt	6.3 KB
08. Demo - Generate Training Batches.mp4	12.7 MB
08. Demo - Generate Training Batches.vtt	8.6 KB
09. Demo - Contruct the Neural Network.mp4	14.8 MB
09. Demo - Contruct the Neural Network.vtt	12.1 KB
10. Demo - Train the Neural Network.mp4	14.9 MB
10. Demo - Train the Neural Network.vtt	8.4 KB
11. Noise Contrastive Estimators to Measure Loss.mp4	7.4 MB
11. Noise Contrastive Estimators to Measure Loss.vtt	7.0 KB
12. Demo - Implementing Noise Contrastive Estimation.mp4	31.5 MB
12. Demo - Implementing Noise Contrastive Estimation.vtt	12.2 KB
13. Summary.mp4	1.4 MB
13. Summary.vtt	1.2 KB
/.../4. Performing Sequence Classification with RNNs/
1. Text as Sequential Data.mp4	6.3 MB
1. Text as Sequential Data.vtt	5.8 KB
2. The Recurrent Neuron.mp4	6.8 MB
2. The Recurrent Neuron.vtt	7.0 KB
3. Input Sequence as a Time Step.mp4	2.9 MB
3. Input Sequence as a Time Step.vtt	2.7 KB
4. Back Propagation Through Time.mp4	12.9 MB
4. Back Propagation Through Time.vtt	11.3 KB
5. Long Term Memory.mp4	7.6 MB
5. Long Term Memory.vtt	7.2 KB
6. The LSTM Cell.mp4	8.1 MB
6. The LSTM Cell.vtt	7.3 KB
/.../5. Implementing Sequence Classification Using RNNs in TensorFlow/
1. Naive Bayes Intuition.mp4	10.7 MB
1. Naive Bayes Intuition.vtt	10.3 KB
2. Demo - Implementing Naive Bayes as a Baseline.mp4	32.5 MB
2. Demo - Implementing Naive Bayes as a Baseline.vtt	15.3 KB
3. Drawbacks of Naive Bayes.mp4	2.3 MB
3. Drawbacks of Naive Bayes.vtt	2.1 KB
4. Demo - Data Preparation for Classification Using RN.mp4	14.4 MB
4. Demo - Data Preparation for Classification Using RN.vtt	7.3 KB
5. Demo - Build and Run the Neural Network.mp4	20.7 MB
5. Demo - Build and Run the Neural Network.vtt	12.5 KB
6. Advantages of RNNs for Sentiment Analysis.mp4	3.6 MB
6. Advantages of RNNs for Sentiment Analysis.vtt	3.1 KB
7. Demo - Use Pre-trained GloVe Embeddings for Classif.mp4	19.8 MB
7. Demo - Use Pre-trained GloVe Embeddings for Classif.vtt	9.4 KB
8. Summary and Further Learning.mp4	3.9 MB
8. Summary and Further Learning.vtt	3.6 KB
/Pluralsight Path. Building Machine Learning Solutions with TensorFlow 2.0 (2020)/
A2. Installation Guide for TensorFlow 2.0 (Omotayo Aina, 2020).chm	587.3 KB
B2. Implement Hyperparameter Tuning for TensorFlow 2.0 (Gaurav Singhal, 2020).chm	502.0 KB
scr.png	151.1 KB
~i.txt	0.9 KB
/.../A1. Getting Started with TensorFlow 2.0 (Janani Ravi, 2020)/
exercise.7z	3.1 MB
playlist.m3u	3.5 KB
~i.txt	2.6 KB
/.../A1. Getting Started with TensorFlow 2.0 (Janani Ravi, 2020)/1. Course Overview/
1. Course Overview.mp4	4.5 MB
1. Course Overview.vtt	3.2 KB
/.../2. Exploring the TensorFlow 2.0 Framework/
1. Version Check.mp4	522.0 KB
1. Version Check.vtt	0.0 KB
2. Prerequisites and Course Outline.mp4	4.0 MB
2. Prerequisites and Course Outline.vtt	3.8 KB
3. TensorFlow 1.x vs. TensorFlow 2.0.mp4	13.0 MB
3. TensorFlow 1.x vs. TensorFlow 2.0.vtt	10.3 KB
4. Introducing Neural Networks.mp4	8.1 MB
4. Introducing Neural Networks.vtt	6.2 KB
5. Neurons and Activation Functions.mp4	14.9 MB
5. Neurons and Activation Functions.vtt	10.5 KB
6. Demo - Install and Set up TensorFlow.mp4	9.9 MB
6. Demo - Install and Set up TensorFlow.vtt	5.3 KB
7. Demo - Tensors and Tensor Operations.mp4	14.5 MB
7. Demo - Tensors and Tensor Operations.vtt	9.2 KB
8. Demo - Variables.mp4	11.6 MB
8. Demo - Variables.vtt	6.5 KB
9. TensorFlow and Keras.mp4	3.6 MB
9. TensorFlow and Keras.vtt	3.1 KB
/.../3. Understanding Dynamic and Static Computation Graphs/
1. The Computation Graph.mp4	6.1 MB
1. The Computation Graph.vtt	4.7 KB
2. Static and Dynamic Computation Graphs.mp4	13.9 MB
2. Static and Dynamic Computation Graphs.vtt	11.0 KB
3. Demo - TensorFlow V1 Sessions to Execute Static Computation Graphs.mp4	15.5 MB
3. Demo - TensorFlow V1 Sessions to Execute Static Computation Graphs.vtt	9.5 KB
4. Demo - TensorBoard to Visualize Graphs.mp4	5.1 MB
4. Demo - TensorBoard to Visualize Graphs.vtt	3.0 KB
5. Demo - Eager Execution.mp4	8.3 MB
5. Demo - Eager Execution.vtt	5.2 KB
6. tf.function.mp4	14.8 MB
6. tf.function.vtt	10.7 KB
7. Demo - Running in Graph Mode Using @tf.function.mp4	12.0 MB
7. Demo - Running in Graph Mode Using @tf.function.vtt	8.0 KB
8. Demo - Statements with Python Side Effects in Graph Mode.mp4	10.2 MB
8. Demo - Statements with Python Side Effects in Graph Mode.vtt	6.4 KB
9. Demo - Instantiating Variables in Graph Mode.mp4	10.9 MB
9. Demo - Instantiating Variables in Graph Mode.vtt	6.5 KB
/.../4. Computing Gradients for Model Training/
1. Gradient Descent.mp4	10.4 MB
1. Gradient Descent.vtt	8.8 KB
2. Forward and Backward Passes.mp4	5.5 MB
2. Forward and Backward Passes.vtt	3.8 KB
3. Calculating Gradients Using Gradient Tape.mp4	9.7 MB
3. Calculating Gradients Using Gradient Tape.vtt	7.8 KB
4. Reverse Mode Automatic Differentiation.mp4	7.6 MB
4. Reverse Mode Automatic Differentiation.vtt	5.8 KB
5. Demo - Gradient Tape for Gradient Calculations.mp4	8.7 MB
5. Demo - Gradient Tape for Gradient Calculations.vtt	5.9 KB
6. Demo - Understanding Gradient Tape Operations.mp4	10.9 MB
6. Demo - Understanding Gradient Tape Operations.vtt	7.4 KB
7. Demo - Simple Regression Using Gradient Calculation.mp4	20.4 MB
7. Demo - Simple Regression Using Gradient Calculation.vtt	10.9 KB
8. Demo - Simple Regression with a Sequential Model.mp4	8.2 MB
8. Demo - Simple Regression with a Sequential Model.vtt	5.6 KB
/.../5. Using the Sequential API in Keras/
1. Introducing the Sequential API in Keras.mp4	10.3 MB
1. Introducing the Sequential API in Keras.vtt	8.6 KB
2. Demo - Exploring and Processing the Life Expectancy Dataset.mp4	21.0 MB
2. Demo - Exploring and Processing the Life Expectancy Dataset.vtt	12.7 KB
3. Demo - Building and Training a Sequential Model.mp4	12.1 MB
3. Demo - Building and Training a Sequential Model.vtt	6.9 KB
4. Demo - TensorBoard to Visualize the Training Process.mp4	18.6 MB
4. Demo - TensorBoard to Visualize the Training Process.vtt	11.0 KB
5. Demo - Configuring Optimizers and Activation Functions.mp4	12.6 MB
5. Demo - Configuring Optimizers and Activation Functions.vtt	7.0 KB
/.../6. Using the Functional API and Model Subclassing in Keras/
1. The Functional API and Model Subclassing.mp4	8.5 MB
1. The Functional API and Model Subclassing.vtt	7.2 KB
2. Demo - Exploring the Heart Disease Dataset.mp4	11.5 MB
2. Demo - Exploring the Heart Disease Dataset.vtt	7.2 KB
3. Demo - Building a Model Using the Keras Functional API.mp4	17.2 MB
3. Demo - Building a Model Using the Keras Functional API.vtt	9.5 KB
4. Demo - Exploring and Processing the Wine Dataset.mp4	10.3 MB
4. Demo - Exploring and Processing the Wine Dataset.vtt	5.6 KB
5. Demo - Building and Training a Multi Class Classification Model Using Model Subclassi.mp4	14.6 MB
5. Demo - Building and Training a Multi Class Classification Model Using Model Subclassi.vtt	8.2 KB
6. Summary and Further Study.mp4	2.3 MB
6. Summary and Further Study.vtt	2.5 KB
/.../B1. Designing Data Pipelines with TensorFlow 2.0 (Chase DeHan, 2020)/
exercise.7z	6.4 MB
playlist.m3u	1.4 KB
~i.txt	1.4 KB
/.../B1. Designing Data Pipelines with TensorFlow 2.0 (Chase DeHan, 2020)/1. Course Overview/
1. Course Overview.mp4	3.3 MB
1. Course Overview.vtt	1.9 KB
/.../2. Evaluating TensorFlow Capabilities/
1. Introduction.mp4	3.4 MB
1. Introduction.vtt	2.9 KB
2. TensorFlow 2.0 Introduction.mp4	5.0 MB
2. TensorFlow 2.0 Introduction.vtt	4.7 KB
3. Migrating to TensorFlow 2.0.mp4	3.8 MB
3. Migrating to TensorFlow 2.0.vtt	3.7 KB
4. Data Pipeline and Model Training.mp4	23.0 MB
4. Data Pipeline and Model Training.vtt	11.8 KB
5. Conclusion.mp4	656.4 KB
5. Conclusion.vtt	0.7 KB
/.../3. Loading Data in TensorFlow/
1. Introduction.mp4	4.2 MB
1. Introduction.vtt	3.6 KB
2. Load from CSV.mp4	22.7 MB
2. Load from CSV.vtt	9.2 KB
3. Load from NumPy and pandas.mp4	23.2 MB
3. Load from NumPy and pandas.vtt	11.2 KB
4. TFExample.mp4	22.0 MB
4. TFExample.vtt	11.9 KB
5. TFRecord.mp4	16.2 MB
5. TFRecord.vtt	9.2 KB
6. Load Image Data.mp4	11.7 MB
6. Load Image Data.vtt	6.1 KB
7. Conclusion.mp4	1.4 MB
7. Conclusion.vtt	1.6 KB
/.../B1. Designing Data Pipelines with TensorFlow 2.0 (Chase DeHan, 2020)/4. Prepping Data/
1. Introduction.mp4	3.4 MB
1. Introduction.vtt	3.1 KB
2. Feature Engineering with pandas.mp4	30.6 MB
2. Feature Engineering with pandas.vtt	17.8 KB
3. Using Zip and Map.mp4	9.8 MB
3. Using Zip and Map.vtt	3.7 KB
4. Load Image Data.mp4	21.4 MB
4. Load Image Data.vtt	9.9 KB
5. Image Data Augmentation.mp4	24.3 MB
5. Image Data Augmentation.vtt	12.1 KB
6. Conclusion.mp4	1.1 MB
6. Conclusion.vtt	1.0 KB
/.../5. Optimizing Performance of Pipelines/
1. Introduction.mp4	3.2 MB
1. Introduction.vtt	2.8 KB
2. Prep Data for Model Training.mp4	14.8 MB
2. Prep Data for Model Training.vtt	7.6 KB
3. Use Keras Sequential API.mp4	19.2 MB
3. Use Keras Sequential API.vtt	9.2 KB
4. Batching and Prefetching.mp4	13.3 MB
4. Batching and Prefetching.vtt	7.2 KB
5. Parallelizing Data Extraction.mp4	10.2 MB
5. Parallelizing Data Extraction.vtt	9.3 KB
6. Conclusion.mp4	1.4 MB
6. Conclusion.vtt	1.4 KB
/.../B3. Building Machine Learning Solutions with TensorFlow.js (Abhishek Kumar, 2020)/
exercise.7z	57.8 MB
playlist.m3u	6.3 KB
~i.txt	2.2 KB
/.../01. Course Overview/
1. Course Overview.mp4	5.7 MB
1. Course Overview.vtt	2.7 KB
/.../B3. Building Machine Learning Solutions with TensorFlow.js (Abhishek Kumar, 2020)/02. Introduction/
1. Introduction.mp4	7.6 MB
1. Introduction.vtt	4.9 KB
2. Why TensorFlow.js.mp4	6.1 MB
2. Why TensorFlow.js.vtt	5.3 KB
3. TensorFlow.js Performance.mp4	4.1 MB
3. TensorFlow.js Performance.vtt	3.5 KB
4. TensorFlow.js Overview.mp4	4.9 MB
4. TensorFlow.js Overview.vtt	4.0 KB
5. Course Demo.mp4	6.8 MB
5. Course Demo.vtt	5.4 KB
6. Course Structure.mp4	3.3 MB
6. Course Structure.vtt	3.4 KB
/.../03. Setting up TensorFlow.js Environment/
1. Introduction.mp4	2.1 MB
1. Introduction.vtt	2.1 KB
2. TensorFlow.js in Browser Using Script Tag.mp4	1.3 MB
2. TensorFlow.js in Browser Using Script Tag.vtt	1.2 KB
3. Demo - Running TensorFlow.js in Browser with Script Tag.mp4	15.6 MB
3. Demo - Running TensorFlow.js in Browser with Script Tag.vtt	7.0 KB
4. TensorFlow.js in Browser Using Package Managers.mp4	4.3 MB
4. TensorFlow.js in Browser Using Package Managers.vtt	3.7 KB
5. Demo - Running TensorFlow.js in Browser Using NPM and Parcel.mp4	22.8 MB
5. Demo - Running TensorFlow.js in Browser Using NPM and Parcel.vtt	8.8 KB
6. Demo - Exploring TensorFlow.js Backends.mp4	19.2 MB
6. Demo - Exploring TensorFlow.js Backends.vtt	7.5 KB
7. Demo - Running TensorFlow.js in Node.js.mp4	16.9 MB
7. Demo - Running TensorFlow.js in Node.js.vtt	6.7 KB
8. Summary.mp4	1.8 MB
8. Summary.vtt	1.7 KB
/.../04. Understanding TensorFlow.js Core Concepts/
1. Introduction.mp4	2.7 MB
1. Introduction.vtt	2.8 KB
2. Tensor Overview.mp4	5.7 MB
2. Tensor Overview.vtt	5.0 KB
3. Demo - Working with Tensors.mp4	6.7 MB
3. Demo - Working with Tensors.vtt	3.1 KB
4. Basic Tensor Operations.mp4	2.7 MB
4. Basic Tensor Operations.vtt	1.7 KB
5. Demo - Performing Basic Tensor Operations.mp4	12.3 MB
5. Demo - Performing Basic Tensor Operations.vtt	5.5 KB
6. Managing Memory with TensorFlow.js.mp4	4.6 MB
6. Managing Memory with TensorFlow.js.vtt	4.6 KB
7. Demo - Managing Memory with TensorFlow.js.mp4	6.2 MB
7. Demo - Managing Memory with TensorFlow.js.vtt	2.7 KB
8. Summary.mp4	2.5 MB
8. Summary.vtt	2.6 KB
/.../05. Preparing Data for Machine Learning Model - Part 1/
1. Introduction.mp4	2.4 MB
1. Introduction.vtt	2.3 KB
2. Machine Learning Workflow.mp4	3.1 MB
2. Machine Learning Workflow.vtt	2.4 KB
3. Toxicity Detection Use Case.mp4	6.7 MB
3. Toxicity Detection Use Case.vtt	5.2 KB
4. Working with TFJS Data.mp4	3.7 MB
4. Working with TFJS Data.vtt	3.6 KB
5. Async JS Programming.mp4	9.5 MB
5. Async JS Programming.vtt	8.0 KB
6. Demo - Reading Data Using TFJS Data.mp4	25.1 MB
6. Demo - Reading Data Using TFJS Data.vtt	10.8 KB
7. Working with TFVis.mp4	2.5 MB
7. Working with TFVis.vtt	1.8 KB
8. Demo - Visualizing Data Using TFVis.mp4	16.6 MB
8. Demo - Visualizing Data Using TFVis.vtt	6.2 KB
9. Summary.mp4	2.6 MB
9. Summary.vtt	2.3 KB
/.../06. Preparing Data for Machine Learning Model - Part 2/
1. Introduction.mp4	2.7 MB
1. Introduction.vtt	2.6 KB
2. Generating Features from Text.mp4	11.0 MB
2. Generating Features from Text.vtt	6.6 KB
3. Demo - Generating TFIDF Features.mp4	38.3 MB
3. Demo - Generating TFIDF Features.vtt	13.2 KB
4. Function Generator.mp4	2.9 MB
4. Function Generator.vtt	2.6 KB
5. Demo - Creating Feature Dataset Using Generators.mp4	6.6 MB
5. Demo - Creating Feature Dataset Using Generators.vtt	3.1 KB
6. Train Validation Test Split.mp4	3.8 MB
6. Train Validation Test Split.vtt	2.7 KB
7. Demo - Splitting Data into Train Validation and Test Datasets.mp4	13.1 MB
7. Demo - Splitting Data into Train Validation and Test Datasets.vtt	5.0 KB
8. Summary.mp4	2.0 MB
8. Summary.vtt	1.9 KB
/.../07. Building, Training, and Evaluating Machine Learning Model/
01. Introduction.mp4	2.9 MB
01. Introduction.vtt	2.7 KB
02. Neural Network Overview.mp4	6.4 MB
02. Neural Network Overview.vtt	5.2 KB
03. Building Neural Network Using Layers API.mp4	4.4 MB
03. Building Neural Network Using Layers API.vtt	3.5 KB
04. Demo - Building Neural Network Using Layers API.mp4	10.4 MB
04. Demo - Building Neural Network Using Layers API.vtt	3.8 KB
05. Training Model Using TensorFlow.js.mp4	5.4 MB
05. Training Model Using TensorFlow.js.vtt	5.0 KB
06. Demo - Training Neural Network Model.mp4	12.3 MB
06. Demo - Training Neural Network Model.vtt	4.3 KB
07. Demo - Visualizing Training Performance.mp4	7.5 MB
07. Demo - Visualizing Training Performance.vtt	2.7 KB
08. Demo - Evaluating Model Performance.mp4	6.3 MB
08. Demo - Evaluating Model Performance.vtt	2.9 KB
09. Model Performance Metrics.mp4	2.5 MB
09. Model Performance Metrics.vtt	2.5 KB
10. Demo - Visualizing Model Performance Metrics.mp4	12.3 MB
10. Demo - Visualizing Model Performance Metrics.vtt	4.5 KB
11. Demo - Running Training in Node.js.mp4	7.9 MB
11. Demo - Running Training in Node.js.vtt	3.1 KB
12. Summary.mp4	2.3 MB
12. Summary.vtt	2.0 KB
/.../08. Saving and Loading Machine Learning Model/
1. Introduction.mp4	1.6 MB
1. Introduction.vtt	1.4 KB
2. Model Export Options.mp4	2.8 MB
2. Model Export Options.vtt	2.2 KB
3. Demo - Exporting Trained Model.mp4	11.1 MB
3. Demo - Exporting Trained Model.vtt	3.8 KB
4. Load Model.mp4	1.8 MB
4. Load Model.vtt	1.4 KB
5. Demo - Loading Trained TensorFlow.js Model.mp4	3.9 MB
5. Demo - Loading Trained TensorFlow.js Model.vtt	1.6 KB
6. Summary.mp4	1.9 MB
6. Summary.vtt	1.5 KB
/.../09. Predicting Using Trained Machine Learning Model/
1. Introduction.mp4	2.3 MB
1. Introduction.vtt	1.8 KB
2. Model Scoring.mp4	3.1 MB
2. Model Scoring.vtt	2.0 KB
3. Demo - Predicting Using Trained TensorFlow.js Model.mp4	12.9 MB
3. Demo - Predicting Using Trained TensorFlow.js Model.vtt	5.1 KB
4. Materialize UI.mp4	1.8 MB
4. Materialize UI.vtt	1.4 KB
5. Demo - Setting up Materialize UI.mp4	13.6 MB
5. Demo - Setting up Materialize UI.vtt	5.6 KB
6. Demo - Integrate Steps with UI.mp4	27.9 MB
6. Demo - Integrate Steps with UI.vtt	13.7 KB
7. TensorFlow.js Converter.mp4	2.6 MB
7. TensorFlow.js Converter.vtt	1.9 KB
8. Demo - Predicting Using Python Exported Model.mp4	30.8 MB
8. Demo - Predicting Using Python Exported Model.vtt	13.1 KB
9. Summary.mp4	2.7 MB
9. Summary.vtt	2.2 KB
/.../10. Using Pre-trained Models with TensorFlow.js/
1. Introduction.mp4	2.0 MB
1. Introduction.vtt	1.9 KB
2. Transfer Learning with TensorFlow.js.mp4	7.3 MB
2. Transfer Learning with TensorFlow.js.vtt	5.2 KB
3. Demo - Creating Features from Universal Sentence Encoder (USE) Model.mp4	17.3 MB
3. Demo - Creating Features from Universal Sentence Encoder (USE) Model.vtt	7.1 KB
4. Demo - Performing Transfer Learning on USE Encoded Features.mp4	15.3 MB
4. Demo - Performing Transfer Learning on USE Encoded Features.vtt	6.0 KB
5. Toxicity Detection Model.mp4	6.1 MB
5. Toxicity Detection Model.vtt	3.7 KB
6. Demo - Using TensorFlow.js Toxicity Detection Model.mp4	12.8 MB
6. Demo - Using TensorFlow.js Toxicity Detection Model.vtt	6.7 KB
7. Summary.mp4	1.7 MB
7. Summary.vtt	1.5 KB
/.../11. Whats Next/
1. Taking Your Journey Forward.mp4	21.6 MB
1. Taking Your Journey Forward.vtt	6.3 KB
/.../C1. Build a Machine Learning Workflow with Keras TensorFlow 2.0 (Janani Ravi, 2020)/
exercise.7z	93.4 MB
playlist.m3u	3.9 KB
~i.txt	2.3 KB
/.../C1. Build a Machine Learning Workflow with Keras TensorFlow 2.0 (Janani Ravi, 2020)/1. Course Overview/
1. Course Overview.mp4	4.2 MB
1. Course Overview.vtt	3.3 KB
/.../2. Understanding Keras Models and Layers/
1. Version Check.mp4	545.2 KB
1. Version Check.vtt	0.0 KB
2. Prerequisites and Course Outline.mp4	4.5 MB
2. Prerequisites and Course Outline.vtt	4.0 KB
3. Introducing Keras.mp4	5.6 MB
3. Introducing Keras.vtt	4.2 KB
4. Supervised Learning.mp4	8.2 MB
4. Supervised Learning.vtt	7.0 KB
5. Unsupervised Learning.mp4	10.6 MB
5. Unsupervised Learning.vtt	7.9 KB
6. Sequential Models.mp4	12.6 MB
6. Sequential Models.vtt	9.6 KB
7. The Functional API.mp4	5.1 MB
7. The Functional API.vtt	4.1 KB
8. Saving and Loading Models.mp4	8.7 MB
8. Saving and Loading Models.vtt	7.7 KB
9. Demo - Install and Set up Tensor Flow.mp4	20.5 MB
9. Demo - Install and Set up Tensor Flow.vtt	9.5 KB
/.../3. Building Regression and Classification Models/
1. Demo - Exploring and Processing the Insurance Dataset.mp4	19.8 MB
1. Demo - Exploring and Processing the Insurance Dataset.vtt	13.2 KB
2. Demo - Training a Simple Sequential Model.mp4	20.8 MB
2. Demo - Training a Simple Sequential Model.vtt	12.2 KB
3. Demo - Configuring Training Behavior Using Callbacks.mp4	15.9 MB
3. Demo - Configuring Training Behavior Using Callbacks.vtt	8.9 KB
4. Demo - Saving Model Architecture and Weights.mp4	12.5 MB
4. Demo - Saving Model Architecture and Weights.vtt	6.3 KB
5. Demo - Loading Saved Models.mp4	9.6 MB
5. Demo - Loading Saved Models.vtt	5.7 KB
6. Demo - Exploring and Processing the Spine Dataset.mp4	12.8 MB
6. Demo - Exploring and Processing the Spine Dataset.vtt	6.9 KB
7. Demo - Build and Train Model Using the Functional API.mp4	20.1 MB
7. Demo - Build and Train Model Using the Functional API.vtt	10.4 KB
8. Demo - Checkpointing Models Using Callbacks.mp4	7.3 MB
8. Demo - Checkpointing Models Using Callbacks.vtt	4.1 KB
9. Demo - Monitoring Models Using TensorBoard.mp4	14.9 MB
9. Demo - Monitoring Models Using TensorBoard.vtt	8.6 KB
/.../4. Building Image Classification Models/
01. Drawbacks of Dense Neural Networks.mp4	5.9 MB
01. Drawbacks of Dense Neural Networks.vtt	4.0 KB
02. Introducing Convolutional Neural Networks.mp4	8.5 MB
02. Introducing Convolutional Neural Networks.vtt	5.6 KB
03. Convolution.mp4	7.8 MB
03. Convolution.vtt	5.5 KB
04. Convolutional Layers.mp4	11.9 MB
04. Convolutional Layers.vtt	8.1 KB
05. Pooling Layers.mp4	8.2 MB
05. Pooling Layers.vtt	5.2 KB
06. CNN Architecture.mp4	6.6 MB
06. CNN Architecture.vtt	4.1 KB
07. Demo - Loading and Preprocessing the Cifar10 Dataset.mp4	17.4 MB
07. Demo - Loading and Preprocessing the Cifar10 Dataset.vtt	10.7 KB
08. Demo - Designing the Convolutional Neural Network.mp4	9.1 MB
08. Demo - Designing the Convolutional Neural Network.vtt	4.8 KB
09. Demo - Training and Prediction Using a CNN.mp4	9.9 MB
09. Demo - Training and Prediction Using a CNN.vtt	5.3 KB
10. Demo - Using Image Transformations and Dropout.mp4	14.6 MB
10. Demo - Using Image Transformations and Dropout.vtt	7.6 KB
/.../5. Building Unsupervised Machine Learning Models/
1. Supervised vs. Unsupervised Learning.mp4	2.6 MB
1. Supervised vs. Unsupervised Learning.vtt	2.1 KB
2. Autoencoders as Unsupervised Machine Learning.mp4	7.1 MB
2. Autoencoders as Unsupervised Machine Learning.vtt	5.8 KB
3. Dimensionality Reduction Using Autoencoders.mp4	11.3 MB
3. Dimensionality Reduction Using Autoencoders.vtt	7.5 KB
4. Demo - Preprocessing Images.mp4	9.0 MB
4. Demo - Preprocessing Images.vtt	5.7 KB
5. Demo - Reconstructing Images Using a Stacked Autoencoder.mp4	11.0 MB
5. Demo - Reconstructing Images Using a Stacked Autoencoder.vtt	6.1 KB
6. Demo - Reconstructing Images Using a CNN Based Autoencoder.mp4	11.9 MB
6. Demo - Reconstructing Images Using a CNN Based Autoencoder.vtt	6.4 KB
/.../6. Implementing Custom Layers and Models/
01. Customizing Layers and Models.mp4	2.2 MB
01. Customizing Layers and Models.vtt	2.1 KB
02. Model Subclassing and Custom Layers.mp4	8.7 MB
02. Model Subclassing and Custom Layers.vtt	6.9 KB
03. Demo - Creating a Custom Layer.mp4	16.2 MB
03. Demo - Creating a Custom Layer.vtt	10.2 KB
04. Demo - Deferring Weight Creation in a Layer.mp4	6.0 MB
04. Demo - Deferring Weight Creation in a Layer.vtt	3.1 KB
05. Demo - Accumulating Losses with Custom Layers.mp4	16.3 MB
05. Demo - Accumulating Losses with Custom Layers.vtt	7.5 KB
06. Demo - Serializing Layers and the Training Parameter.mp4	7.8 MB
06. Demo - Serializing Layers and the Training Parameter.vtt	4.4 KB
07. Demo - Building Custom Models.mp4	10.4 MB
07. Demo - Building Custom Models.vtt	4.7 KB
08. Demo - Building and Training a Regression Model Using Custom Layers.mp4	13.7 MB
08. Demo - Building and Training a Regression Model Using Custom Layers.vtt	6.9 KB
09. Demo - Building and Training a Custom Model with Custom Layers.mp4	12.6 MB
09. Demo - Building and Training a Custom Model with Custom Layers.vtt	5.9 KB
10. Summary and Further Study.mp4	3.0 MB
10. Summary and Further Study.vtt	2.9 KB
/.../C2. Implement Time Series Analysis, Forecasting and Prediction with TensorFlow 2.0 (Chase DeHan, 2020)/
exercise.7z	88.5 MB
playlist.m3u	1.7 KB
~i.txt	1.7 KB
/.../C2. Implement Time Series Analysis, Forecasting and Prediction with TensorFlow 2.0 (Chase DeHan, 2020)/1. Course Overview/
1. Course Overview.mp4	3.1 MB
1. Course Overview.vtt	2.2 KB
/.../2. Understanding Time Series Data/
1. Introduction.mp4	2.8 MB
1. Introduction.vtt	2.7 KB
2. What Is a Time Series.mp4	4.2 MB
2. What Is a Time Series.vtt	4.5 KB
3. Evaluation Metrics.mp4	6.4 MB
3. Evaluation Metrics.vtt	5.0 KB
4. Using a Hold Out.mp4	3.8 MB
4. Using a Hold Out.vtt	3.6 KB
5. Load Data.mp4	4.7 MB
5. Load Data.vtt	2.9 KB
6. Basic Time Series Windows.mp4	6.8 MB
6. Basic Time Series Windows.vtt	5.1 KB
/.../3. Building a Baseline Model/
1. Introduction.mp4	2.5 MB
1. Introduction.vtt	2.1 KB
2. Data Preparation.mp4	4.5 MB
2. Data Preparation.vtt	2.9 KB
3. Split Data.mp4	6.6 MB
3. Split Data.vtt	3.5 KB
4. WindowGenerator Class.mp4	9.3 MB
4. WindowGenerator Class.vtt	6.0 KB
5. Additional Methods in WindowGenerator.mp4	3.2 MB
5. Additional Methods in WindowGenerator.vtt	2.2 KB
6. More Methods.mp4	4.3 MB
6. More Methods.vtt	2.7 KB
7. Single Step Window.mp4	4.6 MB
7. Single Step Window.vtt	2.8 KB
8. Baseline Model Class.mp4	8.3 MB
8. Baseline Model Class.vtt	4.4 KB
9. Linear Model.mp4	8.7 MB
9. Linear Model.vtt	4.9 KB
/.../4. Utilizing Neural Networks/
1. Introduction.mp4	2.3 MB
1. Introduction.vtt	2.3 KB
2. Compile and Fit.mp4	7.9 MB
2. Compile and Fit.vtt	4.7 KB
3. Dense Model.mp4	6.7 MB
3. Dense Model.vtt	3.2 KB
4. Convolutional Model.mp4	8.8 MB
4. Convolutional Model.vtt	4.8 KB
5. Recurrent Neural Networks.mp4	11.3 MB
5. Recurrent Neural Networks.vtt	6.4 KB
/.../5. Expanding the Modeling Approach/
1. Introduction.mp4	2.0 MB
1. Introduction.vtt	1.6 KB
2. Predict Multiple Outputs.mp4	6.9 MB
2. Predict Multiple Outputs.vtt	4.3 KB
3. RNN on Multiple Outputs.mp4	3.4 MB
3. RNN on Multiple Outputs.vtt	2.2 KB
4. Predict Multiple Periods.mp4	6.8 MB
4. Predict Multiple Periods.vtt	4.2 KB
5. Linear Model and Multiple Periods.mp4	5.1 MB
5. Linear Model and Multiple Periods.vtt	2.9 KB
6. Dense Model and Multiple Periods.mp4	2.5 MB
6. Dense Model and Multiple Periods.vtt	1.4 KB
7. CNNs and Multiple Outputs.mp4	6.1 MB
7. CNNs and Multiple Outputs.vtt	3.1 KB
8. LSTM and Multiple Outputs.mp4	6.6 MB
8. LSTM and Multiple Outputs.vtt	3.9 KB
Total files 1275