Deep Learning with TensorFlow | F5425F811BB8D66DE72DF3B9598C9C665BE0C259

Deep Learning with TensorFlow

Name	Deep Learning with TensorFlow 2.0	DOWNLOAD Copy Link
Total Size	2.0 GB
Total Files	231
Last Seen	2025-02-19 23:29
Hash	F5425F811BB8D66DE72DF3B9598C9C665BE0C259

/.../14 Appendix_ Linear Algebra Fundamentals/
104 Why is Linear Algebra Useful_.mp4	151.3 MB
094 What is a Matrix_.en.srt	4.6 KB
094 What is a Matrix_.mp4	35.2 MB
095 Scalars and Vectors.en.srt	4.0 KB
095 Scalars and Vectors.mp4	35.5 MB
096 Linear Algebra and Geometry.en.srt	4.4 KB
096 Linear Algebra and Geometry.mp4	52.2 MB
097 Scalars, Vectors and Matrices in Python.en.srt	6.5 KB
097 Scalars, Vectors and Matrices in Python.mp4	28.0 MB
098 Tensors.en.srt	3.8 KB
098 Tensors.mp4	23.6 MB
099 Addition and Subtraction of Matrices.en.srt	4.3 KB
099 Addition and Subtraction of Matrices.mp4	34.2 MB
100 Errors when Adding Matrices.en.srt	2.7 KB
100 Errors when Adding Matrices.mp4	11.7 MB
101 Transpose of a Matrix.en.srt	5.7 KB
101 Transpose of a Matrix.mp4	39.9 MB
102 Dot Product of Vectors.en.srt	4.6 KB
102 Dot Product of Vectors.mp4	25.1 MB
103 Dot Product of Matrices.en.srt	10.2 KB
103 Dot Product of Matrices.mp4	51.8 MB
104 Why is Linear Algebra Useful_.en.srt	12.5 KB
external-assets-links.txt	1.1 KB
/
TutsNode.com.txt	0.1 KB
[TGx]Downloaded from torrentgalaxy.to .txt	0.6 KB
/.../01 Welcome! Course introduction/
001 Meet your instructors and why you should study machine learning_.en.srt	10.8 KB
001 Meet your instructors and why you should study machine learning_.mp4	110.9 MB
002 What does the course cover_.en.srt	6.6 KB
002 What does the course cover_.mp4	17.1 MB
003 Download All Resources and Important FAQ.html	1.8 KB
/.../02 Introduction to neural networks/
004 Course-Notes-Section-2.pdf	949.9 KB
004 Introduction to neural networks.en.srt	6.3 KB
004 Introduction to neural networks.mp4	14.2 MB
005 Course-Notes-Section-2.pdf	949.9 KB
005 Training the model.en.srt	4.6 KB
005 Training the model.mp4	9.2 MB
006 Course-Notes-Section-2.pdf	949.9 KB
006 Types of machine learning.en.srt	5.6 KB
006 Types of machine learning.mp4	12.8 MB
007 Course-Notes-Section-2.pdf	949.9 KB
007 The linear model.en.srt	4.2 KB
007 The linear model.mp4	9.6 MB
008 Need Help with Linear Algebra_.html	1.7 KB
009 Course-Notes-Section-2.pdf	949.9 KB
009 The linear model. Multiple inputs.en.srt	3.3 KB
009 The linear model. Multiple inputs.mp4	7.9 MB
010 Course-Notes-Section-2.pdf	949.9 KB
010 The linear model. Multiple inputs and multiple outputs.en.srt	5.8 KB
010 The linear model. Multiple inputs and multiple outputs.mp4	40.1 MB
011 Course-Notes-Section-2.pdf	949.9 KB
011 Graphical representation.en.srt	2.9 KB
011 Graphical representation.mp4	6.7 MB
012 Course-Notes-Section-2.pdf	949.9 KB
012 The objective function.en.srt	2.2 KB
012 The objective function.mp4	6.0 MB
013 Course-Notes-Section-2.pdf	949.9 KB
013 L2-norm loss.en.srt	3.0 KB
013 L2-norm loss.mp4	7.6 MB
014 Course-Notes-Section-2.pdf	949.9 KB
014 Cross-entropy loss.en.srt	5.7 KB
014 Cross-entropy loss.mp4	11.9 MB
015 Course-Notes-Section-2.pdf	949.9 KB
015 GD-function-example.xlsx	43.4 KB
015 One parameter gradient descent.en.srt	9.0 KB
015 One parameter gradient descent.mp4	18.6 MB
016 Course-Notes-Section-2.pdf	949.9 KB
016 N-parameter gradient descent.en.srt	8.0 KB
016 N-parameter gradient descent.mp4	41.4 MB
/.../03 Setting up the working environment/
017 Setting up the environment - An introduction - Do not skip, please!.en.srt	1.5 KB
017 Setting up the environment - An introduction - Do not skip, please!.mp4	6.2 MB
018 Why Python and why Jupyter_.en.srt	6.7 KB
018 Why Python and why Jupyter_.mp4	33.6 MB
019 Installing Anaconda.en.srt	4.9 KB
019 Installing Anaconda.mp4	29.8 MB
020 The Jupyter dashboard - part 1.en.srt	3.4 KB
020 The Jupyter dashboard - part 1.mp4	9.1 MB
021 The Jupyter dashboard - part 2.en.srt	7.2 KB
021 The Jupyter dashboard - part 2.mp4	19.7 MB
022 Jupyter Shortcuts.html	1.2 KB
022 Shortcuts-for-Jupyter.pdf	634.0 KB
023 Installing TensorFlow 2.en.srt	6.8 KB
023 Installing TensorFlow 2.mp4	40.6 MB
024 Installing packages - exercise.html	1.1 KB
025 Installing packages - solution.html	1.2 KB
/.../04 Minimal example - your first machine learning algorithm/
026 Minimal example - part 1.en.srt	4.8 KB
026 Minimal example - part 1.mp4	6.9 MB
027 Minimal example - part 2.en.srt	7.3 KB
027 Minimal example - part 2.mp4	11.2 MB
028 Minimal example - part 3.en.srt	4.7 KB
028 Minimal example - part 3.mp4	10.2 MB
029 Minimal example - part 4.en.srt	11.6 KB
029 Minimal example - part 4.mp4	21.8 MB
030 Minimal example - Exercises.html	2.5 KB
external-assets-links.txt	1.8 KB
/.../05 TensorFlow - An introduction/
031 TensorFlow outline.en.srt	5.6 KB
031 TensorFlow outline.mp4	35.2 MB
032 TensorFlow 2 intro.en.srt	3.9 KB
032 TensorFlow 2 intro.mp4	23.1 MB
033 A Note on Coding in TensorFlow.en.srt	1.4 KB
033 A Note on Coding in TensorFlow.mp4	7.1 MB
034 Types of file formats in TensorFlow and data handling.en.srt	3.7 KB
034 Types of file formats in TensorFlow and data handling.mp4	17.2 MB
035 Model layout - inputs, outputs, targets, weights, biases, optimizer and loss.en.srt	8.3 KB
035 Model layout - inputs, outputs, targets, weights, biases, optimizer and loss.mp4	36.4 MB
036 Interpreting the result and extracting the weights and bias.en.srt	6.6 KB
036 Interpreting the result and extracting the weights and bias.mp4	31.7 MB
037 Cutomizing your model.en.srt	4.4 KB
037 Cutomizing your model.mp4	24.0 MB
038 Minimal example with TensorFlow - Exercises.html	2.3 KB
external-assets-links.txt	1.5 KB
/.../06 Going deeper_ Introduction to deep neural networks/
039 Course-Notes-Section-6.pdf	958.9 KB
039 Layers.en.srt	2.6 KB
039 Layers.mp4	5.0 MB
040 Course-Notes-Section-6.pdf	958.9 KB
040 What is a deep net_.en.srt	3.5 KB
040 What is a deep net_.mp4	7.0 MB
041 Understanding deep nets in depth.en.srt	7.1 KB
041 Understanding deep nets in depth.mp4	14.0 MB
042 Why do we need non-linearities_.en.srt	4.1 KB
042 Why do we need non-linearities_.mp4	9.4 MB
043 Activation functions.en.srt	5.5 KB
043 Activation functions.mp4	9.2 MB
044 Softmax activation.en.srt	4.6 KB
044 Softmax activation.mp4	7.7 MB
045 Backpropagation.en.srt	4.7 KB
045 Backpropagation.mp4	11.6 MB
046 Backpropagation - visual representation.en.srt	4.3 KB
046 Backpropagation - visual representation.mp4	7.2 MB
/.../07 Backpropagation. A peek into the Mathematics of Optimization/
047 Backpropagation-a-peek-into-the-Mathematics-of-Optimization.pdf	186.8 KB
047 Backpropagation. A peek into the Mathematics of Optimization.html	1.5 KB
/08 Overfitting/
048 Underfitting and overfitting.en.srt	6.0 KB
048 Underfitting and overfitting.mp4	11.6 MB
049 Underfitting and overfitting - classification.en.srt	2.9 KB
049 Underfitting and overfitting - classification.mp4	7.1 MB
050 Training and validation.en.srt	5.2 KB
050 Training and validation.mp4	9.7 MB
051 Training, validation, and test.en.srt	3.8 KB
051 Training, validation, and test.mp4	7.8 MB
052 N-fold cross validation.en.srt	4.5 KB
052 N-fold cross validation.mp4	7.3 MB
053 Early stopping.en.srt	7.3 KB
053 Early stopping.mp4	9.9 MB
/09 Initialization/
054 Initialization - Introduction.en.srt	3.8 KB
054 Initialization - Introduction.mp4	8.4 MB
055 Types of simple initializations.en.srt	3.9 KB
055 Types of simple initializations.mp4	5.9 MB
056 Xavier initialization.en.srt	4.0 KB
056 Xavier initialization.mp4	6.1 MB
/.../10 Gradient descent and learning rates/
057 Stochastic gradient descent.en.srt	5.2 KB
057 Stochastic gradient descent.mp4	9.8 MB
058 Gradient descent pitfalls.en.srt	3.0 KB
058 Gradient descent pitfalls.mp4	4.5 MB
059 Momentum.en.srt	3.8 KB
059 Momentum.mp4	6.4 MB
060 Learning rate schedules.en.srt	6.4 KB
060 Learning rate schedules.mp4	10.8 MB
061 Learning rate schedules. A picture.en.srt	2.3 KB
061 Learning rate schedules. A picture.mp4	3.3 MB
062 Adaptive learning rate schedules.en.srt	5.5 KB
062 Adaptive learning rate schedules.mp4	9.3 MB
063 Adaptive moment estimation.en.srt	3.6 KB
063 Adaptive moment estimation.mp4	8.1 MB
/11 Preprocessing/
064 Preprocessing introduction.en.srt	4.1 KB
064 Preprocessing introduction.mp4	8.8 MB
065 Basic preprocessing.en.srt	1.8 KB
065 Basic preprocessing.mp4	3.8 MB
066 Standardization.en.srt	6.3 KB
066 Standardization.mp4	8.7 MB
067 Dealing with categorical data.en.srt	3.0 KB
067 Dealing with categorical data.mp4	6.4 MB
068 One-hot and binary encoding.en.srt	5.1 KB
068 One-hot and binary encoding.mp4	6.5 MB
/.../12 The MNIST example/
069 The dataset.en.srt	3.8 KB
069 The dataset.mp4	14.0 MB
070 How to tackle the MNIST.en.srt	3.7 KB
070 How to tackle the MNIST.mp4	19.6 MB
071 Importing the relevant packages and load the data.en.srt	3.3 KB
071 Importing the relevant packages and load the data.mp4	17.1 MB
072 Preprocess the data - create a validation dataset and scale the data.en.srt	6.7 KB
072 Preprocess the data - create a validation dataset and scale the data.mp4	30.5 MB
073 Preprocess the data - scale the test data.html	1.0 KB
074 Preprocess the data - shuffle and batch the data.en.srt	9.8 KB
074 Preprocess the data - shuffle and batch the data.mp4	43.6 MB
075 Preprocess the data - shuffle and batch the data.html	1.0 KB
076 Outline the model.en.srt	7.7 KB
076 Outline the model.mp4	29.6 MB
077 Select the loss and the optimizer.en.srt	3.2 KB
077 Select the loss and the optimizer.mp4	14.6 MB
078 Learning.en.srt	8.5 KB
078 Learning.mp4	42.9 MB
079 MNIST - exercises.html	2.9 KB
080 MNIST - solutions.html	3.1 KB
081 Testing the model.en.srt	6.4 KB
081 Testing the model.mp4	31.0 MB
external-assets-links.txt	2.7 KB
/.../13 Business case/
082 Audiobooks-data.csv	640.2 KB
082 Exploring the dataset and identifying predictors.en.srt	11.3 KB
082 Exploring the dataset and identifying predictors.mp4	69.5 MB
083 Outlining the business case solution.en.srt	2.1 KB
083 Outlining the business case solution.mp4	7.7 MB
084 Balancing the dataset.en.srt	4.8 KB
084 Balancing the dataset.mp4	31.9 MB
085 Audiobooks-data.csv	640.2 KB
085 Preprocessing the data.en.srt	13.0 KB
085 Preprocessing the data.mp4	88.4 MB
086 Audiobooks-data.csv	640.2 KB
086 Preprocessing exercise.html	1.3 KB
087 Load the preprocessed data.en.srt	5.0 KB
087 Load the preprocessed data.mp4	18.4 MB
088 Load the preprocessed data - Exercise.html	1.0 KB
089 Learning and interpreting the result.en.srt	6.7 KB
089 Learning and interpreting the result.mp4	32.7 MB
090 Setting an early stopping mechanism.en.srt	8.3 KB
090 Setting an early stopping mechanism.mp4	52.2 MB
091 Setting an early stopping mechanism - Exercise.html	1.1 KB
092 Testing the model.en.srt	2.2 KB
092 Testing the model.mp4	11.3 MB
093 Final exercise.html	1.3 KB
external-assets-links.txt	1.5 KB
/15 Conclusion/
105 See how much you have learned.en.srt	5.5 KB
105 See how much you have learned.mp4	14.6 MB
106 What’s further out there in the machine and deep learning world.en.srt	2.7 KB
106 What’s further out there in the machine and deep learning world.mp4	6.6 MB
107 An overview of CNNs.en.srt	6.9 KB
107 An overview of CNNs.mp4	11.5 MB
108 How DeepMind uses deep learning.html	2.3 KB
109 An overview of RNNs.en.srt	3.8 KB
109 An overview of RNNs.mp4	5.1 MB
110 An overview of non-NN approaches.en.srt	5.5 KB
110 An overview of non-NN approaches.mp4	8.2 MB
/.../16 Bonus lecture/
111 Bonus lecture_ Next steps.html	4.0 KB
Total files 231