DesireCourse Net Udemy Tensorflow Deep Learning and Artificial Intelligence

DesireCourse Net Udemy Tensorflow Deep Learning and Artificial Intelligence

Name	[DesireCourse.Net] Udemy - Tensorflow 2.0 Deep Learning and Artificial Intelligence	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	7.2 GB
Total Files	246
Hash	FF37CE1043E06BA5A6B030AF42C408CF579F652E

/1. Welcome/
1. Introduction.mp4	41.1 MB
1. Introduction.vtt	5.2 KB
2. Outline.mp4	32.3 MB
2. Outline.vtt	6.5 KB
3. Where to get the code.mp4	32.0 MB
3. Where to get the code.vtt	6.8 KB
/10. GANs (Generative Adversarial Networks)/
1. GAN Theory.mp4	90.7 MB
1. GAN Theory.vtt	18.5 KB
2. GAN Code.mp4	82.0 MB
2. GAN Code.vtt	13.3 KB
/11. Deep Reinforcement Learning (Theory)/
1. Deep Reinforcement Learning Section Introduction.mp4	39.6 MB
1. Deep Reinforcement Learning Section Introduction.vtt	7.7 KB
10. Epsilon-Greedy.mp4	39.4 MB
10. Epsilon-Greedy.vtt	6.7 KB
11. Q-Learning.mp4	64.3 MB
11. Q-Learning.vtt	16.0 KB
12. Deep Q-Learning DQN (pt 1).mp4	58.4 MB
12. Deep Q-Learning DQN (pt 1).vtt	14.7 KB
13. Deep Q-Learning DQN (pt 2).mp4	51.6 MB
13. Deep Q-Learning DQN (pt 2).vtt	11.9 KB
14. How to Learn Reinforcement Learning.mp4	39.3 MB
14. How to Learn Reinforcement Learning.vtt	6.9 KB
2. Elements of a Reinforcement Learning Problem.mp4	102.5 MB
2. Elements of a Reinforcement Learning Problem.vtt	23.4 KB
3. States, Actions, Rewards, Policies.mp4	45.1 MB
3. States, Actions, Rewards, Policies.vtt	10.2 KB
4. Markov Decision Processes (MDPs).mp4	51.3 MB
4. Markov Decision Processes (MDPs).vtt	11.5 KB
5. The Return.mp4	22.0 MB
5. The Return.vtt	5.6 KB
6. Value Functions and the Bellman Equation.mp4	45.4 MB
6. Value Functions and the Bellman Equation.vtt	11.2 KB
7. What does it mean to “learn”.mp4	31.8 MB
7. What does it mean to “learn”.vtt	8.0 KB
8. Solving the Bellman Equation with Reinforcement Learning (pt 1).mp4	40.9 MB
8. Solving the Bellman Equation with Reinforcement Learning (pt 1).vtt	11.3 KB
9. Solving the Bellman Equation with Reinforcement Learning (pt 2).mp4	55.1 MB
9. Solving the Bellman Equation with Reinforcement Learning (pt 2).vtt	13.4 KB
/12. Stock Trading Project with Deep Reinforcement Learning/
1. Reinforcement Learning Stock Trader Introduction.mp4	31.1 MB
1. Reinforcement Learning Stock Trader Introduction.vtt	6.1 KB
2. Data and Environment.mp4	58.7 MB
2. Data and Environment.vtt	14.1 KB
3. Replay Buffer.mp4	25.2 MB
3. Replay Buffer.vtt	6.2 KB
4. Program Design and Layout.mp4	31.2 MB
4. Program Design and Layout.vtt	7.8 KB
5. Code pt 1.mp4	49.1 MB
5. Code pt 1.vtt	6.5 KB
6. Code pt 2.mp4	87.4 MB
6. Code pt 2.vtt	10.5 KB
7. Code pt 3.mp4	65.4 MB
7. Code pt 3.vtt	7.0 KB
8. Code pt 4.mp4	62.0 MB
8. Code pt 4.vtt	7.4 KB
9. Reinforcement Learning Stock Trader Discussion.mp4	19.1 MB
9. Reinforcement Learning Stock Trader Discussion.vtt	4.0 KB
/13. Advanced Tensorflow Usage/
1. What is a Web Service (Tensorflow Serving pt 1).mp4	33.1 MB
1. What is a Web Service (Tensorflow Serving pt 1).vtt	6.9 KB
2. Tensorflow Serving pt 2.mp4	130.5 MB
2. Tensorflow Serving pt 2.vtt	18.2 KB
3. Tensorflow Lite (TFLite).mp4	44.4 MB
3. Tensorflow Lite (TFLite).vtt	9.9 KB
4. Why is Google the King of Distributed Computing.mp4	53.3 MB
4. Why is Google the King of Distributed Computing.vtt	10.2 KB
5. Training with Distributed Strategies.mp4	52.5 MB
5. Training with Distributed Strategies.vtt	7.7 KB
6. Using the TPU.html	1.6 KB
/14. Low-Level Tensorflow/
1. Differences Between Tensorflow 1.x and Tensorflow 2.x.mp4	44.6 MB
1. Differences Between Tensorflow 1.x and Tensorflow 2.x.vtt	11.0 KB
2. Constants and Basic Computation.mp4	52.7 MB
2. Constants and Basic Computation.vtt	8.5 KB
3. Variables and Gradient Tape.mp4	74.0 MB
3. Variables and Gradient Tape.vtt	12.0 KB
4. Build Your Own Custom Model.mp4	73.6 MB
4. Build Your Own Custom Model.vtt	11.9 KB
/15. In-Depth Loss Functions/
1. Mean Squared Error.mp4	39.2 MB
1. Mean Squared Error.vtt	10.1 KB
2. Binary Cross Entropy.mp4	22.5 MB
2. Binary Cross Entropy.vtt	6.5 KB
3. Categorical Cross Entropy.mp4	37.2 MB
3. Categorical Cross Entropy.vtt	8.6 KB
/16. In-Depth Gradient Descent/
1. Gradient Descent.mp4	37.3 MB
1. Gradient Descent.vtt	8.8 KB
2. Stochastic Gradient Descent.mp4	26.3 MB
2. Stochastic Gradient Descent.vtt	4.9 KB
3. Momentum.mp4	41.3 MB
3. Momentum.vtt	7.1 KB
4. Variable and Adaptive Learning Rates.mp4	40.4 MB
4. Variable and Adaptive Learning Rates.vtt	13.6 KB
5. Adam.mp4	44.6 MB
5. Adam.vtt	12.2 KB
/17. Extras/
1. Links to TF2.0 Notebooks.html	8.0 KB
/18. Appendix FAQ/
1. What is the Appendix.mp4	18.9 MB
1. What is the Appendix.vtt	3.4 KB
10. What order should I take your courses in (part 1).mp4	92.4 MB
10. What order should I take your courses in (part 1).vtt	14.5 KB
11. What order should I take your courses in (part 2).mp4	128.6 MB
11. What order should I take your courses in (part 2).vtt	20.7 KB
12. Bonus Where to get discount coupons and FREE deep learning material.mp4	13.9 MB
12. Bonus Where to get discount coupons and FREE deep learning material.vtt	3.0 KB
2. Windows-Focused Environment Setup 2018.mp4	203.4 MB
2. Windows-Focused Environment Setup 2018.vtt	17.8 KB
3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4	174.8 MB
3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt	12.9 KB
4. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4	122.8 MB
4. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt	28.3 KB
5. How to Code Yourself (part 1).mp4	86.1 MB
5. How to Code Yourself (part 1).vtt	19.8 KB
6. How to Code Yourself (part 2).mp4	59.1 MB
6. How to Code Yourself (part 2).vtt	11.7 KB
7. Proof that using Jupyter Notebook is the same as not using it.mp4	81.7 MB
7. Proof that using Jupyter Notebook is the same as not using it.vtt	12.6 KB
8. How to Succeed in this Course (Long Version).mp4	40.8 MB
8. How to Succeed in this Course (Long Version).vtt	13.1 KB
9. Is Theano Dead.mp4	46.5 MB
9. Is Theano Dead.vtt	11.4 KB
/2. Google Colab/
1. Intro to Google Colab, how to use a GPU or TPU for free.mp4	68.3 MB
1. Intro to Google Colab, how to use a GPU or TPU for free.vtt	12.7 KB
2. Tensorflow 2.0 in Google Colab.mp4	53.6 MB
2. Tensorflow 2.0 in Google Colab.vtt	8.5 KB
3. Uploading your own data to Google Colab.mp4	93.4 MB
3. Uploading your own data to Google Colab.vtt	10.7 KB
4. Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn.mp4	46.0 MB
4. Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn.vtt	10.3 KB
/3. Machine Learning and Neurons/
1. What is Machine Learning.mp4	76.7 MB
1. What is Machine Learning.vtt	16.6 KB
2. Code Preparation (Classification Theory).mp4	71.8 MB
2. Code Preparation (Classification Theory).vtt	18.2 KB
3. Classification Notebook.mp4	69.5 MB
3. Classification Notebook.vtt	8.4 KB
4. Code Preparation (Regression Theory).mp4	32.8 MB
4. Code Preparation (Regression Theory).vtt	8.1 KB
5. Regression Notebook.mp4	75.2 MB
5. Regression Notebook.vtt	10.9 KB
6. The Neuron.mp4	51.8 MB
6. The Neuron.vtt	11.2 KB
7. How does a model learn.mp4	57.7 MB
7. How does a model learn.vtt	12.6 KB
8. Making Predictions.mp4	44.0 MB
8. Making Predictions.vtt	7.2 KB
9. Saving and Loading a Model.mp4	37.0 MB
9. Saving and Loading a Model.vtt	4.4 KB
/4. Feedforward Artificial Neural Networks/
1. Artificial Neural Networks Section Introduction.mp4	34.1 MB
1. Artificial Neural Networks Section Introduction.vtt	7.1 KB
2. Forward Propagation.mp4	51.7 MB
2. Forward Propagation.vtt	11.0 KB
3. The Geometrical Picture.mp4	57.5 MB
3. The Geometrical Picture.vtt	10.4 KB
4. Activation Functions.mp4	96.6 MB
4. Activation Functions.vtt	20.3 KB
5. Multiclass Classification.mp4	49.1 MB
5. Multiclass Classification.vtt	9.9 KB
6. How to Represent Images.mp4	84.8 MB
6. How to Represent Images.vtt	14.0 KB
7. Code Preparation (ANN).mp4	58.9 MB
7. Code Preparation (ANN).vtt	14.6 KB
8. ANN for Image Classification.mp4	61.2 MB
8. ANN for Image Classification.vtt	8.9 KB
9. ANN for Regression.mp4	88.0 MB
9. ANN for Regression.vtt	11.5 KB
/5. Convolutional Neural Networks/
1. What is Convolution (part 1).mp4	87.6 MB
1. What is Convolution (part 1).vtt	18.0 KB
10. Batch Normalization.mp4	24.6 MB
10. Batch Normalization.vtt	5.9 KB
11. Improving CIFAR-10 Results.mp4	90.5 MB
11. Improving CIFAR-10 Results.vtt	11.8 KB
2. What is Convolution (part 2).mp4	26.4 MB
2. What is Convolution (part 2).vtt	6.5 KB
3. What is Convolution (part 3).mp4	30.3 MB
3. What is Convolution (part 3).vtt	7.2 KB
4. Convolution on Color Images.mp4	80.8 MB
4. Convolution on Color Images.vtt	18.5 KB
5. CNN Architecture.mp4	95.4 MB
5. CNN Architecture.vtt	25.0 KB
6. CNN Code Preparation.mp4	90.5 MB
6. CNN Code Preparation.vtt	17.6 KB
7. CNN for Fashion MNIST.mp4	54.2 MB
7. CNN for Fashion MNIST.vtt	7.2 KB
8. CNN for CIFAR-10.mp4	36.5 MB
8. CNN for CIFAR-10.vtt	4.9 KB
9. Data Augmentation.mp4	41.1 MB
9. Data Augmentation.vtt	10.1 KB
/6. Recurrent Neural Networks, Time Series, and Sequence Data/
1. Sequence Data.mp4	108.2 MB
1. Sequence Data.vtt	21.4 KB
10. GRU and LSTM (pt 2).mp4	56.2 MB
10. GRU and LSTM (pt 2).vtt	13.0 KB
11. A More Challenging Sequence.mp4	81.4 MB
11. A More Challenging Sequence.vtt	8.6 KB
12. Demo of the Long Distance Problem.mp4	150.1 MB
12. Demo of the Long Distance Problem.vtt	20.6 KB
13. RNN for Image Classification (Theory).mp4	33.0 MB
13. RNN for Image Classification (Theory).vtt	5.4 KB
14. RNN for Image Classification (Code).mp4	28.8 MB
14. RNN for Image Classification (Code).vtt	3.7 KB
15. Stock Return Predictions using LSTMs (pt 1).mp4	83.9 MB
15. Stock Return Predictions using LSTMs (pt 1).vtt	14.0 KB
16. Stock Return Predictions using LSTMs (pt 2).mp4	40.0 MB
16. Stock Return Predictions using LSTMs (pt 2).vtt	5.8 KB
17. Stock Return Predictions using LSTMs (pt 3).mp4	80.5 MB
17. Stock Return Predictions using LSTMs (pt 3).vtt	12.9 KB
2. Forecasting.mp4	49.5 MB
2. Forecasting.vtt	11.4 KB
3. Autoregressive Linear Model for Time Series Prediction.mp4	91.9 MB
3. Autoregressive Linear Model for Time Series Prediction.vtt	12.7 KB
4. Proof that the Linear Model Works.mp4	19.2 MB
4. Proof that the Linear Model Works.vtt	4.1 KB
5. Recurrent Neural Networks.mp4	96.5 MB
5. Recurrent Neural Networks.vtt	22.8 KB
6. RNN Code Preparation.mp4	21.4 MB
6. RNN Code Preparation.vtt	6.4 KB
7. RNN for Time Series Prediction.mp4	91.5 MB
7. RNN for Time Series Prediction.vtt	9.9 KB
8. Paying Attention to Shapes.mp4	67.5 MB
8. Paying Attention to Shapes.vtt	8.8 KB
9. GRU and LSTM (pt 1).mp4	79.8 MB
9. GRU and LSTM (pt 1).vtt	18.8 KB
/7. Natural Language Processing (NLP)/
1. Embeddings.mp4	60.8 MB
1. Embeddings.vtt	14.5 KB
2. Code Preparation (NLP).mp4	66.0 MB
2. Code Preparation (NLP).vtt	15.1 KB
3. Text Preprocessing.mp4	37.9 MB
3. Text Preprocessing.vtt	5.5 KB
4. Text Classification with LSTMs.mp4	63.5 MB
4. Text Classification with LSTMs.vtt	8.8 KB
5. CNNs for Text.mp4	42.8 MB
5. CNNs for Text.vtt	8.6 KB
6. Text Classification with CNNs.mp4	48.7 MB
6. Text Classification with CNNs.vtt	5.9 KB
/8. Recommender Systems/
1. Recommender Systems with Deep Learning Theory.mp4	72.1 MB
1. Recommender Systems with Deep Learning Theory.vtt	15.5 KB
2. Recommender Systems with Deep Learning Code.mp4	61.6 MB
2. Recommender Systems with Deep Learning Code.vtt	10.5 KB
/9. Transfer Learning for Computer Vision/
1. Transfer Learning Theory.mp4	57.8 MB
1. Transfer Learning Theory.vtt	9.6 KB
2. Some Pre-trained Models (VGG, ResNet, Inception, MobileNet).mp4	33.1 MB
2. Some Pre-trained Models (VGG, ResNet, Inception, MobileNet).vtt	6.6 KB
3. Large Datasets and Data Generators.mp4	38.3 MB
3. Large Datasets and Data Generators.vtt	7.9 KB
4. 2 Approaches to Transfer Learning.mp4	21.6 MB
4. 2 Approaches to Transfer Learning.vtt	5.4 KB
5. Transfer Learning Code (pt 1).mp4	69.8 MB
5. Transfer Learning Code (pt 1).vtt	12.4 KB
6. Transfer Learning Code (pt 2).mp4	48.3 MB
6. Transfer Learning Code (pt 2).vtt	9.4 KB
/
[CourseClub.Me].url	0.0 KB
[DesireCourse.Net].url	0.1 KB
Total files 246