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[DesireCourse Com] Udemy - Unsupervised Deep Learning in Python

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[DesireCourse Com] Udemy - Unsupervised Deep Learning in Python

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Name:[DesireCourse Com] Udemy - Unsupervised Deep Learning in Python

Infohash: FA01761607262FC54021026DCE9FB9FA6657B662

Total Size: 2.85 GB

Seeds: 1

Leechers: 6

Stream: Watch Full Movie @ Movie4u

Last Updated: 2024-05-23 18:27:50 (Update Now)

Torrent added: 2019-04-14 02:31:45






Torrent Files List


1. Introduction and Outline (Size: 2.85 GB) (Files: 169)

 1. Introduction and Outline

  1. Introduction and Outline.mp4

3.27 MB

  1. Introduction and Outline.vtt

0.34 KB

  2. Where does this course fit into your deep learning studies.mp4

5.19 MB

  2. Where does this course fit into your deep learning studies.vtt

0.34 KB

  3. How to Succeed in this Course.mp4

6.41 MB

  3. How to Succeed in this Course.vtt

0.34 KB

  4. Where to get the code and data.mp4

26.43 MB

  4. Where to get the code and data.vtt

0.34 KB

  5. Tensorflow or Theano - Your Choice!.mp4

18.93 MB

  5. Tensorflow or Theano - Your Choice!.vtt

0.34 KB

  6. What are the practical applications of unsupervised deep learning.mp4

11.66 MB

  6. What are the practical applications of unsupervised deep learning.vtt

0.34 KB

 10. Basics Review

  1. (Review) Theano Basics.mp4

93.43 MB

  1. (Review) Theano Basics.vtt

6.31 KB

  2. (Review) Theano Neural Network in Code.mp4

87.03 MB

  2. (Review) Theano Neural Network in Code.vtt

3.29 KB

  3. (Review) Tensorflow Basics.mp4

81.47 MB

  3. (Review) Tensorflow Basics.vtt

5.06 KB

  4. (Review) Tensorflow Neural Network in Code.mp4

97.39 MB

  4. (Review) Tensorflow Neural Network in Code.vtt

4.78 KB

  5. (Review) Keras Basics.mp4

27.64 MB

  5. (Review) Keras Basics.vtt

8.05 KB

  6. (Review) Keras in Code pt 1.mp4

66.17 MB

  6. (Review) Keras in Code pt 1.vtt

6.47 KB

  7. (Review) Keras in Code pt 2.mp4

38.67 MB

  7. (Review) Keras in Code pt 2.vtt

4.70 KB

 11. Optional - Legacy RBM Lectures

  1. (Legacy) Restricted Boltzmann Machine Theory.mp4

14.39 MB

  1. (Legacy) Restricted Boltzmann Machine Theory.vtt

10.39 KB

  2. (Legacy) Deriving Conditional Probabilities from Joint Probability.mp4

9.37 MB

  2. (Legacy) Deriving Conditional Probabilities from Joint Probability.vtt

5.72 KB

  3. (Legacy) Contrastive Divergence for RBM Training.mp4

4.85 MB

  3. (Legacy) Contrastive Divergence for RBM Training.vtt

3.01 KB

  4. (Legacy) How to derive the free energy formula.mp4

10.88 MB

  4. (Legacy) How to derive the free energy formula.vtt

5.60 KB

 12. Appendix

  1. What is the Appendix.mp4

5.45 MB

  1. What is the Appendix.vtt

3.28 KB

  10. Python 2 vs Python 3.mp4

7.84 MB

  10. Python 2 vs Python 3.vtt

5.35 KB

  11. Is Theano Dead.mp4

17.82 MB

  11. Is Theano Dead.vtt

11.30 KB

  12. What order should I take your courses in (part 1).mp4

29.33 MB

  12. What order should I take your courses in (part 1).vtt

14.09 KB

  13. What order should I take your courses in (part 2).mp4

37.62 MB

  13. What order should I take your courses in (part 2).vtt

20.24 KB

  2. BONUS Where to get Udemy coupons and FREE deep learning material.mp4

4.03 MB

  2. BONUS Where to get Udemy coupons and FREE deep learning material.vtt

2.99 KB

  3. Windows-Focused Environment Setup 2018.mp4

186.39 MB

  3. Windows-Focused Environment Setup 2018.vtt

17.39 KB

  4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4

43.92 MB

  4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt

12.40 KB

  5. How to Code by Yourself (part 1).mp4

24.53 MB

  5. How to Code by Yourself (part 1).vtt

19.78 KB

  6. How to Code by Yourself (part 2).mp4

14.80 MB

  6. How to Code by Yourself (part 2).vtt

11.62 KB

  7. How to Succeed in this Course (Long Version).mp4

18.31 MB

  7. How to Succeed in this Course (Long Version).vtt

12.79 KB

  8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4

38.95 MB

  8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt

27.77 KB

  9. Proof that using Jupyter Notebook is the same as not using it.mp4

78.25 MB

  9. Proof that using Jupyter Notebook is the same as not using it.vtt

78.26 MB

 2. Principal Components Analysis

  1. What does PCA do.mp4

27.79 MB

  1. What does PCA do.vtt

4.96 KB

  10. SVD (Singular Value Decomposition).mp4

42.47 MB

  10. SVD (Singular Value Decomposition).vtt

10.33 KB

  2. How does PCA work.mp4

50.93 MB

  2. How does PCA work.vtt

12.37 KB

  3. Why does PCA work (PCA derivation).mp4

51.32 MB

  3. Why does PCA work (PCA derivation).vtt

0.34 KB

  4. PCA only rotates.mp4

16.45 MB

  4. PCA only rotates.vtt

0.34 KB

  5. MNIST visualization, finding the optimal number of principal components.mp4

9.39 MB

  5. MNIST visualization, finding the optimal number of principal components.vtt

3.33 KB

  6. PCA implementation.mp4

32.09 MB

  6. PCA implementation.vtt

0.34 KB

  7. PCA for NLP.mp4

16.62 MB

  7. PCA for NLP.vtt

3.89 KB

  8. PCA objective function.mp4

3.68 MB

  8. PCA objective function.vtt

2.28 KB

  9. PCA Application Naive Bayes.mp4

53.65 MB

  9. PCA Application Naive Bayes.vtt

10.78 KB

 3. t-SNE (t-distributed Stochastic Neighbor Embedding)

  1. t-SNE Theory.mp4

7.90 MB

  1. t-SNE Theory.vtt

4.78 KB

  2. t-SNE Visualization.mp4

13.03 MB

  2. t-SNE Visualization.vtt

4.82 KB

  3. t-SNE on the Donut.mp4

15.10 MB

  3. t-SNE on the Donut.vtt

2.23 KB

  4. t-SNE on XOR.mp4

9.31 MB

  4. t-SNE on XOR.vtt

3.64 KB

  5. t-SNE on MNIST.mp4

4.35 MB

  5. t-SNE on MNIST.vtt

1.59 KB

 4. Autoencoders

  1. Autoencoders.mp4

5.82 MB

  1. Autoencoders.vtt

3.94 KB

  10. Deep Autoencoder Visualization Description.mp4

2.46 MB

  10. Deep Autoencoder Visualization Description.vtt

2.00 KB

  11. Deep Autoencoder Visualization in Code.mp4

27.85 MB

  11. Deep Autoencoder Visualization in Code.vtt

6.67 KB

  12. An Autoencoder in 1 Line of Code.mp4

24.94 MB

  12. An Autoencoder in 1 Line of Code.vtt

5.08 KB

  2. Denoising Autoencoders.mp4

3.44 MB

  2. Denoising Autoencoders.vtt

2.26 KB

  3. Stacked Autoencoders.mp4

6.60 MB

  3. Stacked Autoencoders.vtt

4.24 KB

  4. Writing the autoencoder class in code (Theano).mp4

38.52 MB

  4. Writing the autoencoder class in code (Theano).vtt

6.08 KB

  5. Testing our Autoencoder (Theano).mp4

11.36 MB

  5. Testing our Autoencoder (Theano).vtt

2.67 KB

  6. Writing the deep neural network class in code (Theano).mp4

41.97 MB

  6. Writing the deep neural network class in code (Theano).vtt

6.37 KB

  7. Autoencoder in Code (Tensorflow).mp4

24.45 MB

  7. Autoencoder in Code (Tensorflow).vtt

8.17 KB

  8. Testing greedy layer-wise autoencoder training vs. pure backpropagation.mp4

18.53 MB

  8. Testing greedy layer-wise autoencoder training vs. pure backpropagation.vtt

1.86 KB

  9. Cross Entropy vs. KL Divergence.mp4

7.42 MB

  9. Cross Entropy vs. KL Divergence.vtt

5.48 KB

 5. Restricted Boltzmann Machines

  1. Basic Outline for RBMs.mp4

32.98 MB

  1. Basic Outline for RBMs.vtt

5.64 KB

  10. RBM in Code (Theano) with Greedy Layer-Wise Training on MNIST.mp4

47.76 MB

  10. RBM in Code (Theano) with Greedy Layer-Wise Training on MNIST.vtt

6.77 KB

  11. RBM in Code (Tensorflow).mp4

13.70 MB

  11. RBM in Code (Tensorflow).vtt

0.34 KB

  2. Introduction to RBMs.mp4

39.44 MB

  2. Introduction to RBMs.vtt

0.34 KB

  3. Motivation Behind RBMs.mp4

34.00 MB

  3. Motivation Behind RBMs.vtt

0.34 KB

  4. Intractability.mp4

12.92 MB

  4. Intractability.vtt

0.34 KB

  5. Neural Network Equations.mp4

31.71 MB

  5. Neural Network Equations.vtt

7.42 KB

  6. Training an RBM (part 1).mp4

49.08 MB

  6. Training an RBM (part 1).vtt

11.76 KB

  7. Training an RBM (part 2).mp4

27.34 MB

  7. Training an RBM (part 2).vtt

6.44 KB

  8. Training an RBM (part 3) - Free Energy.mp4

27.58 MB

  8. Training an RBM (part 3) - Free Energy.vtt

7.03 KB

  9. RBM Greedy Layer-Wise Pretraining.mp4

23.62 MB

  9. RBM Greedy Layer-Wise Pretraining.vtt

5.19 KB

 6. The Vanishing Gradient Problem

  1. The Vanishing Gradient Problem Description.mp4

5.20 MB

  1. The Vanishing Gradient Problem Description.vtt

0.34 KB

  2. The Vanishing Gradient Problem Demo in Code.mp4

31.29 MB

  2. The Vanishing Gradient Problem Demo in Code.vtt

0.34 KB

 7. Extras + Visualizing what features a neural network has learned

  1. Exercises on feature visualization and interpretation.mp4

3.75 MB

  1. Exercises on feature visualization and interpretation.vtt

0.34 KB

 8. Applications to NLP (Natural Language Processing)

  1. Application of PCA and SVD to NLP (Natural Language Processing).mp4

3.93 MB

  1. Application of PCA and SVD to NLP (Natural Language Processing).vtt

0.34 KB

  2. Latent Semantic Analysis in Code.mp4

25.62 MB

  2. Latent Semantic Analysis in Code.vtt

0.34 KB

  3. Application of t-SNE + K-Means Finding Clusters of Related Words.mp4

25.99 MB

  3. Application of t-SNE + K-Means Finding Clusters of Related Words.vtt

0.34 KB

 9. Applications to Recommender Systems

  1. Recommender Systems Section Introduction.mp4

68.17 MB

  1. Recommender Systems Section Introduction.vtt

0.34 KB

  10. Recommender RBM Code Speedup.mp4

82.95 MB

  10. Recommender RBM Code Speedup.vtt

82.96 MB

  2. Why Autoencoders and RBMs work.mp4

38.19 MB

  2. Why Autoencoders and RBMs work.vtt

0.34 KB

  3. Data Preparation and Logistics.mp4

21.21 MB

  3. Data Preparation and Logistics.vtt

0.34 KB

  4. AutoRec.mp4

48.90 MB

  4. AutoRec.vtt

0.34 KB

  5. AutoRec in Code.mp4

102.28 MB

  5. AutoRec in Code.vtt

12.62 KB

  6. Categorical RBM for Recommender System Ratings.mp4

47.59 MB

  6. Categorical RBM for Recommender System Ratings.vtt

12.05 KB

  7. Recommender RBM Code pt 1.mp4

70.42 MB

  7. Recommender RBM Code pt 1.vtt

8.74 KB

  8. Recommender RBM Code pt 2.mp4

39.58 MB

  8. Recommender RBM Code pt 2.vtt

4.63 KB

  9. Recommender RBM Code pt 3.mp4

128.54 MB

  9. Recommender RBM Code pt 3.vtt

11.98 KB

 [DesireCourse.Com].url

0.05 KB
 

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