Tutorialsplanet NET Udemy Tensorflow Deep Learning and Artificial Intelligence

Tutorialsplanet NET Udemy Tensorflow Deep Learning and Artificial Intelligence

Name	[Tutorialsplanet.NET] Udemy - Tensorflow 2.0 Deep Learning and Artificial Intelligence	DOWNLOAD Copy Link
Total Size	7.3 GB
Total Files	275
Hash	B733E822845D9436C9BAA67FB34349568FE58F8A

/1. Welcome/
1. Introduction.mp4	36.5 MB
1. Introduction.srt	5.8 KB
2. Outline.mp4	77.3 MB
2. Outline.srt	17.5 KB
3. Where to get the code.mp4	66.0 MB
3. Where to get the code.srt	15.7 KB
3.1 Colab Notebooks.html	0.2 KB
3.2 Github Link.html	0.1 KB
[Tutorialsplanet.NET].url	0.1 KB
/10. GANs (Generative Adversarial Networks)/
1. GAN Theory.mp4	91.4 MB
1. GAN Theory.srt	21.2 KB
2. GAN Code.mp4	82.1 MB
2. GAN Code.srt	15.2 KB
/11. Deep Reinforcement Learning (Theory)/
1. Deep Reinforcement Learning Section Introduction.mp4	39.9 MB
1. Deep Reinforcement Learning Section Introduction.srt	8.8 KB
10. Epsilon-Greedy.mp4	42.1 MB
10. Epsilon-Greedy.srt	7.7 KB
11. Q-Learning.mp4	64.8 MB
11. Q-Learning.srt	18.3 KB
12. Deep Q-Learning DQN (pt 1).mp4	59.0 MB
12. Deep Q-Learning DQN (pt 1).srt	16.8 KB
13. Deep Q-Learning DQN (pt 2).mp4	52.0 MB
13. Deep Q-Learning DQN (pt 2).srt	13.5 KB
14. How to Learn Reinforcement Learning.mp4	39.5 MB
14. How to Learn Reinforcement Learning.srt	7.8 KB
2. Elements of a Reinforcement Learning Problem.mp4	103.4 MB
2. Elements of a Reinforcement Learning Problem.srt	26.8 KB
3. States, Actions, Rewards, Policies.mp4	45.4 MB
3. States, Actions, Rewards, Policies.srt	11.6 KB
4. Markov Decision Processes (MDPs).mp4	51.7 MB
4. Markov Decision Processes (MDPs).srt	13.0 KB
5. The Return.mp4	22.2 MB
5. The Return.srt	6.4 KB
6. Value Functions and the Bellman Equation.mp4	45.7 MB
6. Value Functions and the Bellman Equation.srt	12.8 KB
7. What does it mean to “learn”.mp4	33.3 MB
7. What does it mean to “learn”.srt	9.1 KB
8. Solving the Bellman Equation with Reinforcement Learning (pt 1).mp4	44.8 MB
8. Solving the Bellman Equation with Reinforcement Learning (pt 1).srt	12.7 KB
9. Solving the Bellman Equation with Reinforcement Learning (pt 2).mp4	55.5 MB
9. Solving the Bellman Equation with Reinforcement Learning (pt 2).srt	15.2 KB
/12. Stock Trading Project with Deep Reinforcement Learning/
1. Reinforcement Learning Stock Trader Introduction.mp4	27.3 MB
1. Reinforcement Learning Stock Trader Introduction.srt	7.0 KB
10. Help! Why is the code slower on my machine.mp4	44.5 MB
10. Help! Why is the code slower on my machine.srt	12.0 KB
2. Data and Environment.mp4	53.4 MB
2. Data and Environment.srt	16.1 KB
3. Replay Buffer.mp4	25.2 MB
3. Replay Buffer.srt	7.1 KB
4. Program Design and Layout.mp4	27.2 MB
4. Program Design and Layout.srt	8.8 KB
5. Code pt 1.mp4	41.5 MB
5. Code pt 1.srt	7.4 KB
6. Code pt 2.mp4	71.3 MB
6. Code pt 2.srt	12.0 KB
7. Code pt 3.mp4	54.6 MB
7. Code pt 3.srt	7.9 KB
8. Code pt 4.mp4	55.1 MB
8. Code pt 4.srt	8.6 KB
9. Reinforcement Learning Stock Trader Discussion.mp4	17.4 MB
9. Reinforcement Learning Stock Trader Discussion.srt	4.5 KB
/13. Advanced Tensorflow Usage/
1. What is a Web Service (Tensorflow Serving pt 1).mp4	29.1 MB
1. What is a Web Service (Tensorflow Serving pt 1).srt	7.9 KB
2. Tensorflow Serving pt 2.mp4	110.1 MB
2. Tensorflow Serving pt 2.srt	20.9 KB
3. Tensorflow Lite (TFLite).mp4	44.7 MB
3. Tensorflow Lite (TFLite).srt	11.3 KB
4. Why is Google the King of Distributed Computing.mp4	47.1 MB
4. Why is Google the King of Distributed Computing.srt	11.5 KB
5. Training with Distributed Strategies.mp4	45.7 MB
5. Training with Distributed Strategies.srt	8.7 KB
6. Using the TPU.mp4	47.4 MB
6. Using the TPU.srt	7.1 KB
[Tutorialsplanet.NET].url	0.1 KB
/14. Low-Level Tensorflow/
1. Differences Between Tensorflow 1.x and Tensorflow 2.x.mp4	40.6 MB
1. Differences Between Tensorflow 1.x and Tensorflow 2.x.srt	12.5 KB
2. Constants and Basic Computation.mp4	42.3 MB
2. Constants and Basic Computation.srt	9.9 KB
3. Variables and Gradient Tape.mp4	58.8 MB
3. Variables and Gradient Tape.srt	13.9 KB
4. Build Your Own Custom Model.mp4	61.4 MB
4. Build Your Own Custom Model.srt	13.6 KB
/15. In-Depth Loss Functions/
1. Mean Squared Error.mp4	35.4 MB
1. Mean Squared Error.srt	11.5 KB
2. Binary Cross Entropy.mp4	24.8 MB
2. Binary Cross Entropy.srt	7.4 KB
3. Categorical Cross Entropy.mp4	33.2 MB
3. Categorical Cross Entropy.srt	9.9 KB
/16. In-Depth Gradient Descent/
1. Gradient Descent.mp4	36.6 MB
1. Gradient Descent.srt	10.0 KB
2. Stochastic Gradient Descent.mp4	24.1 MB
2. Stochastic Gradient Descent.srt	5.5 KB
3. Momentum.mp4	35.9 MB
3. Momentum.srt	8.0 KB
4. Variable and Adaptive Learning Rates.mp4	36.5 MB
4. Variable and Adaptive Learning Rates.srt	15.5 KB
5. Adam (pt 1).mp4	57.8 MB
5. Adam (pt 1).srt	17.1 KB
6. Adam (pt 2).mp4	55.3 MB
6. Adam (pt 2).srt	14.8 KB
/17. Extras/
1. How to Choose Hyperparameters.mp4	39.8 MB
1. How to Choose Hyperparameters.srt	8.9 KB
2. Where Are The Exercises.mp4	27.2 MB
2. Where Are The Exercises.srt	5.5 KB
3. Links to TF2.0 Notebooks.html	8.3 KB
[Tutorialsplanet.NET].url	0.1 KB
/18/
1. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4	157.9 MB
1. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt	15.0 KB
2. Anaconda Environment Setup.mp4	189.7 MB
2. Anaconda Environment Setup.srt	20.4 KB
3. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.mp4	175.4 MB
3. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.srt	32.8 KB
/19. Extra Help With Python Coding for Beginners (FAQ by Student Request)/
1. Beginner's Coding Tips.mp4	79.4 MB
1. Beginner's Coding Tips.srt	19.5 KB
2. How to Code Yourself (part 1).mp4	75.3 MB
2. How to Code Yourself (part 1).srt	22.7 KB
3. How to Code Yourself (part 2).mp4	51.5 MB
3. How to Code Yourself (part 2).srt	13.3 KB
4. Proof that using Jupyter Notebook is the same as not using it.mp4	72.8 MB
4. Proof that using Jupyter Notebook is the same as not using it.srt	14.6 KB
5. Is Theano Dead.mp4	42.7 MB
5. Is Theano Dead.srt	12.9 KB
/2. Google Colab/
1. Intro to Google Colab, how to use a GPU or TPU for free.mp4	56.5 MB
1. Intro to Google Colab, how to use a GPU or TPU for free.srt	14.5 KB
2. Tensorflow 2.0 in Google Colab.mp4	42.6 MB
2. Tensorflow 2.0 in Google Colab.srt	9.7 KB
3. Uploading your own data to Google Colab.mp4	77.2 MB
3. Uploading your own data to Google Colab.srt	12.3 KB
4. Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn.mp4	40.8 MB
4. Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn.srt	11.8 KB
5. How to Succeed in this Course.mp4	45.9 MB
5. How to Succeed in this Course.srt	8.5 KB
/20/
1. How to Succeed in this Course (Long Version).mp4	36.9 MB
1. How to Succeed in this Course (Long Version).srt	15.0 KB
2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4	110.7 MB
2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt	32.4 KB
3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4	83.6 MB
3. Machine Learning and AI Prerequisite Roadmap (pt 1).srt	16.5 KB
4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4	113.4 MB
4. Machine Learning and AI Prerequisite Roadmap (pt 2).srt	23.6 KB
[Tutorialsplanet.NET].url	0.1 KB
/21. Appendix FAQ Finale/
1. What is the Appendix.mp4	17.2 MB
1. What is the Appendix.srt	3.8 KB
2. BONUS Lecture.mp4	39.6 MB
2. BONUS Lecture.srt	8.1 KB
/3. Machine Learning and Neurons/
1. What is Machine Learning.mp4	68.7 MB
1. What is Machine Learning.srt	18.9 KB
10. Why Keras.mp4	27.8 MB
10. Why Keras.srt	5.9 KB
11. Suggestion Box.mp4	28.4 MB
11. Suggestion Box.srt	4.9 KB
2. Code Preparation (Classification Theory).mp4	62.7 MB
2. Code Preparation (Classification Theory).srt	20.7 KB
3. Classification Notebook.mp4	57.2 MB
3. Classification Notebook.srt	9.6 KB
4. Code Preparation (Regression Theory).mp4	28.6 MB
4. Code Preparation (Regression Theory).srt	9.3 KB
5. Regression Notebook.mp4	60.3 MB
5. Regression Notebook.srt	12.4 KB
6. The Neuron.mp4	44.6 MB
6. The Neuron.srt	12.8 KB
7. How does a model learn.mp4	50.3 MB
7. How does a model learn.srt	14.3 KB
8. Making Predictions.mp4	35.5 MB
8. Making Predictions.srt	8.2 KB
9. Saving and Loading a Model.mp4	31.2 MB
9. Saving and Loading a Model.srt	5.0 KB
/4. Feedforward Artificial Neural Networks/
1. Artificial Neural Networks Section Introduction.mp4	31.3 MB
1. Artificial Neural Networks Section Introduction.srt	8.1 KB
10. ANN for Regression.mp4	72.6 MB
10. ANN for Regression.srt	13.1 KB
2. Beginners Rejoice The Math in This Course is Optional.mp4	71.8 MB
2. Beginners Rejoice The Math in This Course is Optional.srt	17.4 KB
3. Forward Propagation.mp4	49.0 MB
3. Forward Propagation.srt	12.5 KB
4. The Geometrical Picture.mp4	59.2 MB
4. The Geometrical Picture.srt	11.8 KB
5. Activation Functions.mp4	84.4 MB
5. Activation Functions.srt	23.2 KB
6. Multiclass Classification.mp4	43.4 MB
6. Multiclass Classification.srt	11.2 KB
7. How to Represent Images.mp4	73.9 MB
7. How to Represent Images.srt	16.0 KB
8. Code Preparation (ANN).mp4	53.4 MB
8. Code Preparation (ANN).srt	16.7 KB
9. ANN for Image Classification.mp4	50.0 MB
9. ANN for Image Classification.srt	10.2 KB
/5. Convolutional Neural Networks/
1. What is Convolution (part 1).mp4	83.6 MB
1. What is Convolution (part 1).srt	20.6 KB
10. Batch Normalization.mp4	22.1 MB
10. Batch Normalization.srt	6.7 KB
11. Improving CIFAR-10 Results.mp4	76.5 MB
11. Improving CIFAR-10 Results.srt	13.5 KB
2. What is Convolution (part 2).mp4	23.3 MB
2. What is Convolution (part 2).srt	7.4 KB
3. What is Convolution (part 3).mp4	29.0 MB
3. What is Convolution (part 3).srt	8.2 KB
4. Convolution on Color Images.mp4	72.8 MB
4. Convolution on Color Images.srt	21.0 KB
5. CNN Architecture.mp4	84.5 MB
5. CNN Architecture.srt	28.6 KB
6. CNN Code Preparation.mp4	80.6 MB
6. CNN Code Preparation.srt	20.1 KB
7. CNN for Fashion MNIST.mp4	44.9 MB
7. CNN for Fashion MNIST.srt	8.2 KB
8. CNN for CIFAR-10.mp4	31.1 MB
8. CNN for CIFAR-10.srt	5.5 KB
9. Data Augmentation.mp4	36.6 MB
9. Data Augmentation.srt	11.5 KB
[Tutorialsplanet.NET].url	0.1 KB
/6. Recurrent Neural Networks, Time Series, and Sequence Data/
1. Sequence Data.mp4	94.5 MB
1. Sequence Data.srt	24.6 KB
10. GRU and LSTM (pt 2).mp4	52.8 MB
10. GRU and LSTM (pt 2).srt	14.6 KB
11. A More Challenging Sequence.mp4	67.8 MB
11. A More Challenging Sequence.srt	9.8 KB
12. Demo of the Long Distance Problem.mp4	130.1 MB
12. Demo of the Long Distance Problem.srt	23.6 KB
13. RNN for Image Classification (Theory).mp4	30.5 MB
13. RNN for Image Classification (Theory).srt	6.1 KB
14. RNN for Image Classification (Code).mp4	24.4 MB
14. RNN for Image Classification (Code).srt	4.3 KB
15. Stock Return Predictions using LSTMs (pt 1).mp4	70.4 MB
15. Stock Return Predictions using LSTMs (pt 1).srt	16.1 KB
16. Stock Return Predictions using LSTMs (pt 2).mp4	34.6 MB
16. Stock Return Predictions using LSTMs (pt 2).srt	6.7 KB
17. Stock Return Predictions using LSTMs (pt 3).mp4	70.6 MB
17. Stock Return Predictions using LSTMs (pt 3).srt	14.8 KB
18. Other Ways to Forecast.mp4	29.7 MB
18. Other Ways to Forecast.srt	7.4 KB
2. Forecasting.mp4	49.0 MB
2. Forecasting.srt	13.7 KB
3. Autoregressive Linear Model for Time Series Prediction.mp4	75.2 MB
3. Autoregressive Linear Model for Time Series Prediction.srt	14.6 KB
4. Proof that the Linear Model Works.mp4	17.0 MB
4. Proof that the Linear Model Works.srt	4.7 KB
5. Recurrent Neural Networks.mp4	87.0 MB
5. Recurrent Neural Networks.srt	26.2 KB
6. RNN Code Preparation.mp4	19.3 MB
6. RNN Code Preparation.srt	7.3 KB
7. RNN for Time Series Prediction.mp4	77.7 MB
7. RNN for Time Series Prediction.srt	11.5 KB
8. Paying Attention to Shapes.mp4	55.0 MB
8. Paying Attention to Shapes.srt	10.1 KB
9. GRU and LSTM (pt 1).mp4	83.7 MB
9. GRU and LSTM (pt 1).srt	23.3 KB
/7. Natural Language Processing (NLP)/
1. Embeddings.mp4	55.1 MB
1. Embeddings.srt	16.6 KB
2. Code Preparation (NLP).mp4	59.8 MB
2. Code Preparation (NLP).srt	17.2 KB
3. Text Preprocessing.mp4	30.2 MB
3. Text Preprocessing.srt	6.3 KB
4. Text Classification with LSTMs.mp4	53.1 MB
4. Text Classification with LSTMs.srt	10.0 KB
5. CNNs for Text.mp4	42.4 MB
5. CNNs for Text.srt	10.3 KB
6. Text Classification with CNNs.mp4	41.5 MB
6. Text Classification with CNNs.srt	6.8 KB
/8. Recommender Systems/
1. Recommender Systems with Deep Learning Theory.mp4	72.0 MB
1. Recommender Systems with Deep Learning Theory.srt	17.8 KB
2. Recommender Systems with Deep Learning Code.mp4	61.7 MB
2. Recommender Systems with Deep Learning Code.srt	12.0 KB
/9. Transfer Learning for Computer Vision/
1. Transfer Learning Theory.mp4	57.8 MB
1. Transfer Learning Theory.srt	10.9 KB
2. Some Pre-trained Models (VGG, ResNet, Inception, MobileNet).mp4	33.1 MB
2. Some Pre-trained Models (VGG, ResNet, Inception, MobileNet).srt	7.5 KB
3. Large Datasets and Data Generators.mp4	38.3 MB
3. Large Datasets and Data Generators.srt	9.0 KB
4. 2 Approaches to Transfer Learning.mp4	21.6 MB
4. 2 Approaches to Transfer Learning.srt	6.1 KB
5. Transfer Learning Code (pt 1).mp4	69.8 MB
5. Transfer Learning Code (pt 1).srt	14.1 KB
6. Transfer Learning Code (pt 2).mp4	48.3 MB
6. Transfer Learning Code (pt 2).srt	10.7 KB
/
[Tutorialsplanet.NET].url	0.1 KB
Total files 275