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[DesireCourse.Com] Udemy - Unsupervised Deep Learning in Python

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File Name
Size
1. Introduction and Outline/1. Introduction and Outline.mp4
3.3 MB
1. Introduction and Outline/1. Introduction and Outline.vtt
351 B
1. Introduction and Outline/2. Where does this course fit into your deep learning studies.mp4
5.2 MB
1. Introduction and Outline/2. Where does this course fit into your deep learning studies.vtt
351 B
1. Introduction and Outline/3. How to Succeed in this Course.mp4
6.4 MB
1. Introduction and Outline/3. How to Succeed in this Course.vtt
351 B
1. Introduction and Outline/4. Where to get the code and data.mp4
26 MB
1. Introduction and Outline/4. Where to get the code and data.vtt
351 B
1. Introduction and Outline/5. Tensorflow or Theano - Your Choice!.mp4
19 MB
1. Introduction and Outline/5. Tensorflow or Theano - Your Choice!.vtt
351 B
1. Introduction and Outline/6. What are the practical applications of unsupervised deep learning.mp4
12 MB
1. Introduction and Outline/6. What are the practical applications of unsupervised deep learning.vtt
351 B
10. Basics Review/1. (Review) Theano Basics.mp4
93 MB
10. Basics Review/1. (Review) Theano Basics.vtt
6.3 kB
10. Basics Review/2. (Review) Theano Neural Network in Code.mp4
87 MB
10. Basics Review/2. (Review) Theano Neural Network in Code.vtt
3.3 kB
10. Basics Review/3. (Review) Tensorflow Basics.mp4
82 MB
10. Basics Review/3. (Review) Tensorflow Basics.vtt
5.1 kB
10. Basics Review/4. (Review) Tensorflow Neural Network in Code.mp4
97 MB
10. Basics Review/4. (Review) Tensorflow Neural Network in Code.vtt
4.8 kB
10. Basics Review/5. (Review) Keras Basics.mp4
28 MB
10. Basics Review/5. (Review) Keras Basics.vtt
8.0 kB
10. Basics Review/6. (Review) Keras in Code pt 1.mp4
66 MB
10. Basics Review/6. (Review) Keras in Code pt 1.vtt
6.5 kB
10. Basics Review/7. (Review) Keras in Code pt 2.mp4
39 MB
10. Basics Review/7. (Review) Keras in Code pt 2.vtt
4.7 kB
11. Optional - Legacy RBM Lectures/1. (Legacy) Restricted Boltzmann Machine Theory.mp4
14 MB
11. Optional - Legacy RBM Lectures/1. (Legacy) Restricted Boltzmann Machine Theory.vtt
10 kB
11. Optional - Legacy RBM Lectures/2. (Legacy) Deriving Conditional Probabilities from Joint Probability.mp4
9.4 MB
11. Optional - Legacy RBM Lectures/2. (Legacy) Deriving Conditional Probabilities from Joint Probability.vtt
5.7 kB
11. Optional - Legacy RBM Lectures/3. (Legacy) Contrastive Divergence for RBM Training.mp4
4.8 MB
11. Optional - Legacy RBM Lectures/3. (Legacy) Contrastive Divergence for RBM Training.vtt
3.0 kB
11. Optional - Legacy RBM Lectures/4. (Legacy) How to derive the free energy formula.mp4
11 MB
11. Optional - Legacy RBM Lectures/4. (Legacy) How to derive the free energy formula.vtt
5.6 kB
12. Appendix/1. What is the Appendix.mp4
5.5 MB
12. Appendix/1. What is the Appendix.vtt
3.3 kB
12. Appendix/10. Python 2 vs Python 3.mp4
7.8 MB
12. Appendix/10. Python 2 vs Python 3.vtt
5.4 kB
12. Appendix/11. Is Theano Dead.mp4
18 MB
12. Appendix/11. Is Theano Dead.vtt
11 kB
12. Appendix/12. What order should I take your courses in (part 1).mp4
29 MB
12. Appendix/12. What order should I take your courses in (part 1).vtt
14 kB
12. Appendix/13. What order should I take your courses in (part 2).mp4
38 MB
12. Appendix/13. What order should I take your courses in (part 2).vtt
20 kB
12. Appendix/2. BONUS Where to get Udemy coupons and FREE deep learning material.mp4
4.0 MB
12. Appendix/2. BONUS Where to get Udemy coupons and FREE deep learning material.vtt
3.0 kB
12. Appendix/3. Windows-Focused Environment Setup 2018.mp4
186 MB
12. Appendix/3. Windows-Focused Environment Setup 2018.vtt
17 kB
12. Appendix/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4
44 MB
12. Appendix/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt
12 kB
12. Appendix/5. How to Code by Yourself (part 1).mp4
24 MB
12. Appendix/5. How to Code by Yourself (part 1).vtt
20 kB
12. Appendix/6. How to Code by Yourself (part 2).mp4
15 MB
12. Appendix/6. How to Code by Yourself (part 2).vtt
12 kB
12. Appendix/7. How to Succeed in this Course (Long Version).mp4
18 MB
12. Appendix/7. How to Succeed in this Course (Long Version).vtt
13 kB
12. Appendix/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4
39 MB
12. Appendix/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt
28 kB
12. Appendix/9. Proof that using Jupyter Notebook is the same as not using it.mp4
78 MB
12. Appendix/9. Proof that using Jupyter Notebook is the same as not using it.vtt
78 MB
2. Principal Components Analysis/1. What does PCA do.mp4
28 MB
2. Principal Components Analysis/1. What does PCA do.vtt
5.0 kB
2. Principal Components Analysis/10. SVD (Singular Value Decomposition).mp4
42 MB
2. Principal Components Analysis/10. SVD (Singular Value Decomposition).vtt
10 kB
2. Principal Components Analysis/2. How does PCA work.mp4
51 MB
2. Principal Components Analysis/2. How does PCA work.vtt
12 kB
2. Principal Components Analysis/3. Why does PCA work (PCA derivation).mp4
51 MB
2. Principal Components Analysis/3. Why does PCA work (PCA derivation).vtt
351 B
2. Principal Components Analysis/4. PCA only rotates.mp4
16 MB
2. Principal Components Analysis/4. PCA only rotates.vtt
351 B
2. Principal Components Analysis/5. MNIST visualization, finding the optimal number of principal components.mp4
9.4 MB
2. Principal Components Analysis/5. MNIST visualization, finding the optimal number of principal components.vtt
3.3 kB
2. Principal Components Analysis/6. PCA implementation.mp4
32 MB
2. Principal Components Analysis/6. PCA implementation.vtt
351 B
2. Principal Components Analysis/7. PCA for NLP.mp4
17 MB
2. Principal Components Analysis/7. PCA for NLP.vtt
3.9 kB
2. Principal Components Analysis/8. PCA objective function.mp4
3.7 MB
2. Principal Components Analysis/8. PCA objective function.vtt
2.3 kB
2. Principal Components Analysis/9. PCA Application Naive Bayes.mp4
54 MB
2. Principal Components Analysis/9. PCA Application Naive Bayes.vtt
11 kB
3. t-SNE (t-distributed Stochastic Neighbor Embedding)/1. t-SNE Theory.mp4
7.9 MB
3. t-SNE (t-distributed Stochastic Neighbor Embedding)/1. t-SNE Theory.vtt
4.8 kB
3. t-SNE (t-distributed Stochastic Neighbor Embedding)/2. t-SNE Visualization.mp4
13 MB
3. t-SNE (t-distributed Stochastic Neighbor Embedding)/2. t-SNE Visualization.vtt
4.8 kB
3. t-SNE (t-distributed Stochastic Neighbor Embedding)/3. t-SNE on the Donut.mp4
15 MB
3. t-SNE (t-distributed Stochastic Neighbor Embedding)/3. t-SNE on the Donut.vtt
2.2 kB
3. t-SNE (t-distributed Stochastic Neighbor Embedding)/4. t-SNE on XOR.mp4
9.3 MB
3. t-SNE (t-distributed Stochastic Neighbor Embedding)/4. t-SNE on XOR.vtt
3.6 kB
3. t-SNE (t-distributed Stochastic Neighbor Embedding)/5. t-SNE on MNIST.mp4
4.4 MB
3. t-SNE (t-distributed Stochastic Neighbor Embedding)/5. t-SNE on MNIST.vtt
1.6 kB
4. Autoencoders/1. Autoencoders.mp4
5.8 MB
4. Autoencoders/1. Autoencoders.vtt
3.9 kB
4. Autoencoders/10. Deep Autoencoder Visualization Description.mp4
2.5 MB
4. Autoencoders/10. Deep Autoencoder Visualization Description.vtt
2.0 kB
4. Autoencoders/11. Deep Autoencoder Visualization in Code.mp4
28 MB
4. Autoencoders/11. Deep Autoencoder Visualization in Code.vtt
6.7 kB
4. Autoencoders/12. An Autoencoder in 1 Line of Code.mp4
25 MB
4. Autoencoders/12. An Autoencoder in 1 Line of Code.vtt
5.1 kB
4. Autoencoders/2. Denoising Autoencoders.mp4
3.4 MB
4. Autoencoders/2. Denoising Autoencoders.vtt
2.3 kB
4. Autoencoders/3. Stacked Autoencoders.mp4
6.6 MB
4. Autoencoders/3. Stacked Autoencoders.vtt
4.2 kB
4. Autoencoders/4. Writing the autoencoder class in code (Theano).mp4
38 MB
4. Autoencoders/4. Writing the autoencoder class in code (Theano).vtt
6.1 kB
4. Autoencoders/5. Testing our Autoencoder (Theano).mp4
11 MB
4. Autoencoders/5. Testing our Autoencoder (Theano).vtt
2.7 kB
4. Autoencoders/6. Writing the deep neural network class in code (Theano).mp4
42 MB
4. Autoencoders/6. Writing the deep neural network class in code (Theano).vtt
6.4 kB
4. Autoencoders/7. Autoencoder in Code (Tensorflow).mp4
24 MB
4. Autoencoders/7. Autoencoder in Code (Tensorflow).vtt
8.2 kB
4. Autoencoders/8. Testing greedy layer-wise autoencoder training vs. pure backpropagation.mp4
18 MB
4. Autoencoders/8. Testing greedy layer-wise autoencoder training vs. pure backpropagation.vtt
1.9 kB
4. Autoencoders/9. Cross Entropy vs. KL Divergence.mp4
7.4 MB
4. Autoencoders/9. Cross Entropy vs. KL Divergence.vtt
5.5 kB
5. Restricted Boltzmann Machines/1. Basic Outline for RBMs.mp4
33 MB
5. Restricted Boltzmann Machines/1. Basic Outline for RBMs.vtt
5.6 kB
5. Restricted Boltzmann Machines/10. RBM in Code (Theano) with Greedy Layer-Wise Training on MNIST.mp4
48 MB
5. Restricted Boltzmann Machines/10. RBM in Code (Theano) with Greedy Layer-Wise Training on MNIST.vtt
6.8 kB
5. Restricted Boltzmann Machines/11. RBM in Code (Tensorflow).mp4
14 MB
5. Restricted Boltzmann Machines/11. RBM in Code (Tensorflow).vtt
351 B
5. Restricted Boltzmann Machines/2. Introduction to RBMs.mp4
39 MB
5. Restricted Boltzmann Machines/2. Introduction to RBMs.vtt
351 B
5. Restricted Boltzmann Machines/3. Motivation Behind RBMs.mp4
34 MB
5. Restricted Boltzmann Machines/3. Motivation Behind RBMs.vtt
351 B
5. Restricted Boltzmann Machines/4. Intractability.mp4
13 MB
5. Restricted Boltzmann Machines/4. Intractability.vtt
351 B
5. Restricted Boltzmann Machines/5. Neural Network Equations.mp4
32 MB
5. Restricted Boltzmann Machines/5. Neural Network Equations.vtt
7.4 kB
5. Restricted Boltzmann Machines/6. Training an RBM (part 1).mp4
49 MB
5. Restricted Boltzmann Machines/6. Training an RBM (part 1).vtt
12 kB
5. Restricted Boltzmann Machines/7. Training an RBM (part 2).mp4
27 MB
5. Restricted Boltzmann Machines/7. Training an RBM (part 2).vtt
6.4 kB
5. Restricted Boltzmann Machines/8. Training an RBM (part 3) - Free Energy.mp4
28 MB
5. Restricted Boltzmann Machines/8. Training an RBM (part 3) - Free Energy.vtt
7.0 kB
5. Restricted Boltzmann Machines/9. RBM Greedy Layer-Wise Pretraining.mp4
24 MB
5. Restricted Boltzmann Machines/9. RBM Greedy Layer-Wise Pretraining.vtt
5.2 kB
6. The Vanishing Gradient Problem/1. The Vanishing Gradient Problem Description.mp4
5.2 MB
6. The Vanishing Gradient Problem/1. The Vanishing Gradient Problem Description.vtt
351 B
6. The Vanishing Gradient Problem/2. The Vanishing Gradient Problem Demo in Code.mp4
31 MB
6. The Vanishing Gradient Problem/2. The Vanishing Gradient Problem Demo in Code.vtt
351 B
7. Extras + Visualizing what features a neural network has learned/1. Exercises on feature visualization and interpretation.mp4
3.8 MB
7. Extras + Visualizing what features a neural network has learned/1. Exercises on feature visualization and interpretation.vtt
351 B
8. Applications to NLP (Natural Language Processing)/1. Application of PCA and SVD to NLP (Natural Language Processing).mp4
3.9 MB
8. Applications to NLP (Natural Language Processing)/1. Application of PCA and SVD to NLP (Natural Language Processing).vtt
351 B
8. Applications to NLP (Natural Language Processing)/2. Latent Semantic Analysis in Code.mp4
26 MB
8. Applications to NLP (Natural Language Processing)/2. Latent Semantic Analysis in Code.vtt
351 B
8. Applications to NLP (Natural Language Processing)/3. Application of t-SNE + K-Means Finding Clusters of Related Words.mp4
26 MB
8. Applications to NLP (Natural Language Processing)/3. Application of t-SNE + K-Means Finding Clusters of Related Words.vtt
351 B
9. Applications to Recommender Systems/1. Recommender Systems Section Introduction.mp4
68 MB
9. Applications to Recommender Systems/1. Recommender Systems Section Introduction.vtt
351 B
9. Applications to Recommender Systems/10. Recommender RBM Code Speedup.mp4
83 MB
9. Applications to Recommender Systems/10. Recommender RBM Code Speedup.vtt
83 MB
9. Applications to Recommender Systems/2. Why Autoencoders and RBMs work.mp4
38 MB
9. Applications to Recommender Systems/2. Why Autoencoders and RBMs work.vtt
351 B
9. Applications to Recommender Systems/3. Data Preparation and Logistics.mp4
21 MB
9. Applications to Recommender Systems/3. Data Preparation and Logistics.vtt
351 B
9. Applications to Recommender Systems/4. AutoRec.mp4
49 MB
9. Applications to Recommender Systems/4. AutoRec.vtt
351 B
9. Applications to Recommender Systems/5. AutoRec in Code.mp4
102 MB
9. Applications to Recommender Systems/5. AutoRec in Code.vtt
13 kB
9. Applications to Recommender Systems/6. Categorical RBM for Recommender System Ratings.mp4
48 MB
9. Applications to Recommender Systems/6. Categorical RBM for Recommender System Ratings.vtt
12 kB
9. Applications to Recommender Systems/7. Recommender RBM Code pt 1.mp4
70 MB
9. Applications to Recommender Systems/7. Recommender RBM Code pt 1.vtt
8.7 kB
9. Applications to Recommender Systems/8. Recommender RBM Code pt 2.mp4
40 MB
9. Applications to Recommender Systems/8. Recommender RBM Code pt 2.vtt
4.6 kB
9. Applications to Recommender Systems/9. Recommender RBM Code pt 3.mp4
128 MB
9. Applications to Recommender Systems/9. Recommender RBM Code pt 3.vtt
12 kB
[DesireCourse.Com].url
51 B