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[DesireCourse.Com] Udemy - Unsupervised Deep Learning in Python
大小 2.85 GB
文件数 169
Info Hash: FA01761607262FC54021026DCE9FB9FA6657B662
收录时间 2025-12-13 19:19:24
更新时间 2025-12-19 23:24:24
文件列表 (169)
1. Introduction and Outline/1. Introduction and Outline.mp4
3.27 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
5.19 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
6.41 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
26.43 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
18.93 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
11.66 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
93.43 MB
10. Basics Review/1. (Review) Theano Basics.vtt
6.31 KB
10. Basics Review/2. (Review) Theano Neural Network in Code.mp4
87.03 MB
10. Basics Review/2. (Review) Theano Neural Network in Code.vtt
3.29 KB
10. Basics Review/3. (Review) Tensorflow Basics.mp4
81.47 MB
10. Basics Review/3. (Review) Tensorflow Basics.vtt
5.06 KB
10. Basics Review/4. (Review) Tensorflow Neural Network in Code.mp4
97.39 MB
10. Basics Review/4. (Review) Tensorflow Neural Network in Code.vtt
4.78 KB
10. Basics Review/5. (Review) Keras Basics.mp4
27.64 MB
10. Basics Review/5. (Review) Keras Basics.vtt
8.05 KB
10. Basics Review/6. (Review) Keras in Code pt 1.mp4
66.17 MB
10. Basics Review/6. (Review) Keras in Code pt 1.vtt
6.47 KB
10. Basics Review/7. (Review) Keras in Code pt 2.mp4
38.67 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
14.39 MB
11. Optional - Legacy RBM Lectures/1. (Legacy) Restricted Boltzmann Machine Theory.vtt
10.39 KB
11. Optional - Legacy RBM Lectures/2. (Legacy) Deriving Conditional Probabilities from Joint Probability.mp4
9.37 MB
11. Optional - Legacy RBM Lectures/2. (Legacy) Deriving Conditional Probabilities from Joint Probability.vtt
5.72 KB
11. Optional - Legacy RBM Lectures/3. (Legacy) Contrastive Divergence for RBM Training.mp4
4.85 MB
11. Optional - Legacy RBM Lectures/3. (Legacy) Contrastive Divergence for RBM Training.vtt
3.01 KB
11. Optional - Legacy RBM Lectures/4. (Legacy) How to derive the free energy formula.mp4
10.88 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
5.45 MB
12. Appendix/1. What is the Appendix.vtt
3.28 KB
12. Appendix/10. Python 2 vs Python 3.mp4
7.84 MB
12. Appendix/10. Python 2 vs Python 3.vtt
5.35 KB
12. Appendix/11. Is Theano Dead.mp4
17.82 MB
12. Appendix/11. Is Theano Dead.vtt
11.3 KB
12. Appendix/12. What order should I take your courses in (part 1).mp4
29.33 MB
12. Appendix/12. What order should I take your courses in (part 1).vtt
14.09 KB
12. Appendix/13. What order should I take your courses in (part 2).mp4
37.62 MB
12. Appendix/13. What order should I take your courses in (part 2).vtt
20.24 KB
12. Appendix/2. BONUS Where to get Udemy coupons and FREE deep learning material.mp4
4.03 MB
12. Appendix/2. BONUS Where to get Udemy coupons and FREE deep learning material.vtt
2.99 KB
12. Appendix/3. Windows-Focused Environment Setup 2018.mp4
186.39 MB
12. Appendix/3. Windows-Focused Environment Setup 2018.vtt
17.39 KB
12. Appendix/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4
43.92 MB
12. Appendix/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt
12.4 KB
12. Appendix/5. How to Code by Yourself (part 1).mp4
24.53 MB
12. Appendix/5. How to Code by Yourself (part 1).vtt
19.78 KB
12. Appendix/6. How to Code by Yourself (part 2).mp4
14.8 MB
12. Appendix/6. How to Code by Yourself (part 2).vtt
11.62 KB
12. Appendix/7. How to Succeed in this Course (Long Version).mp4
18.31 MB
12. Appendix/7. How to Succeed in this Course (Long Version).vtt
12.79 KB
12. Appendix/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4
38.95 MB
12. Appendix/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt
27.77 KB
12. Appendix/9. Proof that using Jupyter Notebook is the same as not using it.mp4
78.25 MB
12. Appendix/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
2. Principal Components Analysis/1. What does PCA do.vtt
4.96 KB
2. Principal Components Analysis/10. SVD (Singular Value Decomposition).mp4
42.47 MB
2. Principal Components Analysis/10. SVD (Singular Value Decomposition).vtt
10.33 KB
2. Principal Components Analysis/2. How does PCA work.mp4
50.93 MB
2. Principal Components Analysis/2. How does PCA work.vtt
12.37 KB
2. Principal Components Analysis/3. Why does PCA work (PCA derivation).mp4
51.32 MB
2. Principal Components Analysis/3. Why does PCA work (PCA derivation).vtt
351 B
2. Principal Components Analysis/4. PCA only rotates.mp4
16.45 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
9.39 MB
2. Principal Components Analysis/5. MNIST visualization, finding the optimal number of principal components.vtt
3.33 KB
2. Principal Components Analysis/6. PCA implementation.mp4
32.09 MB
2. Principal Components Analysis/6. PCA implementation.vtt
351 B
2. Principal Components Analysis/7. PCA for NLP.mp4
16.62 MB
2. Principal Components Analysis/7. PCA for NLP.vtt
3.89 KB
2. Principal Components Analysis/8. PCA objective function.mp4
3.68 MB
2. Principal Components Analysis/8. PCA objective function.vtt
2.28 KB
2. Principal Components Analysis/9. PCA Application Naive Bayes.mp4
53.65 MB
2. Principal Components Analysis/9. PCA Application Naive Bayes.vtt
10.78 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
4.78 KB
3. t-SNE (t-distributed Stochastic Neighbor Embedding)/2. t-SNE Visualization.mp4
13.03 MB
3. t-SNE (t-distributed Stochastic Neighbor Embedding)/2. t-SNE Visualization.vtt
4.82 KB
3. t-SNE (t-distributed Stochastic Neighbor Embedding)/3. t-SNE on the Donut.mp4
15.1 MB
3. t-SNE (t-distributed Stochastic Neighbor Embedding)/3. t-SNE on the Donut.vtt
2.23 KB
3. t-SNE (t-distributed Stochastic Neighbor Embedding)/4. t-SNE on XOR.mp4
9.31 MB
3. t-SNE (t-distributed Stochastic Neighbor Embedding)/4. t-SNE on XOR.vtt
3.64 KB
3. t-SNE (t-distributed Stochastic Neighbor Embedding)/5. t-SNE on MNIST.mp4
4.35 MB
3. t-SNE (t-distributed Stochastic Neighbor Embedding)/5. t-SNE on MNIST.vtt
1.59 KB
4. Autoencoders/1. Autoencoders.mp4
5.82 MB
4. Autoencoders/1. Autoencoders.vtt
3.94 KB
4. Autoencoders/10. Deep Autoencoder Visualization Description.mp4
2.46 MB
4. Autoencoders/10. Deep Autoencoder Visualization Description.vtt
2 KB
4. Autoencoders/11. Deep Autoencoder Visualization in Code.mp4
27.85 MB
4. Autoencoders/11. Deep Autoencoder Visualization in Code.vtt
6.67 KB
4. Autoencoders/12. An Autoencoder in 1 Line of Code.mp4
24.94 MB
4. Autoencoders/12. An Autoencoder in 1 Line of Code.vtt
5.08 KB
4. Autoencoders/2. Denoising Autoencoders.mp4
3.44 MB
4. Autoencoders/2. Denoising Autoencoders.vtt
2.26 KB
4. Autoencoders/3. Stacked Autoencoders.mp4
6.6 MB
4. Autoencoders/3. Stacked Autoencoders.vtt
4.24 KB
4. Autoencoders/4. Writing the autoencoder class in code (Theano).mp4
38.52 MB
4. Autoencoders/4. Writing the autoencoder class in code (Theano).vtt
6.08 KB
4. Autoencoders/5. Testing our Autoencoder (Theano).mp4
11.36 MB
4. Autoencoders/5. Testing our Autoencoder (Theano).vtt
2.67 KB
4. Autoencoders/6. Writing the deep neural network class in code (Theano).mp4
41.97 MB
4. Autoencoders/6. Writing the deep neural network class in code (Theano).vtt
6.37 KB
4. Autoencoders/7. Autoencoder in Code (Tensorflow).mp4
24.45 MB
4. Autoencoders/7. Autoencoder in Code (Tensorflow).vtt
8.17 KB
4. Autoencoders/8. Testing greedy layer-wise autoencoder training vs. pure backpropagation.mp4
18.53 MB
4. Autoencoders/8. Testing greedy layer-wise autoencoder training vs. pure backpropagation.vtt
1.86 KB
4. Autoencoders/9. Cross Entropy vs. KL Divergence.mp4
7.42 MB
4. Autoencoders/9. Cross Entropy vs. KL Divergence.vtt
5.48 KB
5. Restricted Boltzmann Machines/1. Basic Outline for RBMs.mp4
32.98 MB
5. Restricted Boltzmann Machines/1. Basic Outline for RBMs.vtt
5.64 KB
5. Restricted Boltzmann Machines/10. RBM in Code (Theano) with Greedy Layer-Wise Training on MNIST.mp4
47.76 MB
5. Restricted Boltzmann Machines/10. RBM in Code (Theano) with Greedy Layer-Wise Training on MNIST.vtt
6.77 KB
5. Restricted Boltzmann Machines/11. RBM in Code (Tensorflow).mp4
13.7 MB
5. Restricted Boltzmann Machines/11. RBM in Code (Tensorflow).vtt
351 B
5. Restricted Boltzmann Machines/2. Introduction to RBMs.mp4
39.44 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
12.92 MB
5. Restricted Boltzmann Machines/4. Intractability.vtt
351 B
5. Restricted Boltzmann Machines/5. Neural Network Equations.mp4
31.71 MB
5. Restricted Boltzmann Machines/5. Neural Network Equations.vtt
7.42 KB
5. Restricted Boltzmann Machines/6. Training an RBM (part 1).mp4
49.08 MB
5. Restricted Boltzmann Machines/6. Training an RBM (part 1).vtt
11.76 KB
5. Restricted Boltzmann Machines/7. Training an RBM (part 2).mp4
27.34 MB
5. Restricted Boltzmann Machines/7. Training an RBM (part 2).vtt
6.44 KB
5. Restricted Boltzmann Machines/8. Training an RBM (part 3) - Free Energy.mp4
27.58 MB
5. Restricted Boltzmann Machines/8. Training an RBM (part 3) - Free Energy.vtt
7.03 KB
5. Restricted Boltzmann Machines/9. RBM Greedy Layer-Wise Pretraining.mp4
23.62 MB
5. Restricted Boltzmann Machines/9. RBM Greedy Layer-Wise Pretraining.vtt
5.19 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
31.29 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
3.75 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
3.93 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
25.62 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
25.99 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
68.17 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
82.95 MB
9. Applications to Recommender Systems/10. Recommender RBM Code Speedup.vtt
82.96 MB
9. Applications to Recommender Systems/2. Why Autoencoders and RBMs work.mp4
38.19 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
21.21 MB
9. Applications to Recommender Systems/3. Data Preparation and Logistics.vtt
351 B
9. Applications to Recommender Systems/4. AutoRec.mp4
48.9 MB
9. Applications to Recommender Systems/4. AutoRec.vtt
351 B
9. Applications to Recommender Systems/5. AutoRec in Code.mp4
102.28 MB
9. Applications to Recommender Systems/5. AutoRec in Code.vtt
12.62 KB
9. Applications to Recommender Systems/6. Categorical RBM for Recommender System Ratings.mp4
47.59 MB
9. Applications to Recommender Systems/6. Categorical RBM for Recommender System Ratings.vtt
12.05 KB
9. Applications to Recommender Systems/7. Recommender RBM Code pt 1.mp4
70.42 MB
9. Applications to Recommender Systems/7. Recommender RBM Code pt 1.vtt
8.74 KB
9. Applications to Recommender Systems/8. Recommender RBM Code pt 2.mp4
39.58 MB
9. Applications to Recommender Systems/8. Recommender RBM Code pt 2.vtt
4.63 KB
9. Applications to Recommender Systems/9. Recommender RBM Code pt 3.mp4
128.54 MB
9. Applications to Recommender Systems/9. Recommender RBM Code pt 3.vtt
11.98 KB
[DesireCourse.Com].url
51 B
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