Udemy - Unsupervised Deep Learning In Python

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[DesireCourse.Com] Udemy - Unsupervised Deep Learning in Python 1. Introduction and Outline
  • 1. Introduction and Outline.mp4 (3.3 MB)
  • 1. Introduction and Outline.vtt (0.3 KB)
  • 2. Where does this course fit into your deep learning studies.mp4 (5.2 MB)
  • 2. Where does this course fit into your deep learning studies.vtt (0.3 KB)
  • 3. How to Succeed in this Course.mp4 (6.4 MB)
  • 3. How to Succeed in this Course.vtt (0.3 KB)
  • 4. Where to get the code and data.mp4 (26.4 MB)
  • 4. Where to get the code and data.vtt (0.3 KB)
  • 5. Tensorflow or Theano - Your Choice!.mp4 (18.9 MB)
  • 5. Tensorflow or Theano - Your Choice!.vtt (0.3 KB)
  • 6. What are the practical applications of unsupervised deep learning.mp4 (11.7 MB)
  • 6. What are the practical applications of unsupervised deep learning.vtt (0.3 KB)
10. Basics Review
  • 1. (Review) Theano Basics.mp4 (93.4 MB)
  • 1. (Review) Theano Basics.vtt (6.3 KB)
  • 2. (Review) Theano Neural Network in Code.mp4 (87.0 MB)
  • 2. (Review) Theano Neural Network in Code.vtt (3.3 KB)
  • 3. (Review) Tensorflow Basics.mp4 (81.5 MB)
  • 3. (Review) Tensorflow Basics.vtt (5.1 KB)
  • 4. (Review) Tensorflow Neural Network in Code.mp4 (97.4 MB)
  • 4. (Review) Tensorflow Neural Network in Code.vtt (4.8 KB)
  • 5. (Review) Keras Basics.mp4 (27.6 MB)
  • 5. (Review) Keras Basics.vtt (8.0 KB)
  • 6. (Review) Keras in Code pt 1.mp4 (66.2 MB)
  • 6. (Review) Keras in Code pt 1.vtt (6.5 KB)
  • 7. (Review) Keras in Code pt 2.mp4 (38.7 MB)
  • 7. (Review) Keras in Code pt 2.vtt (4.7 KB)
11. Optional - Legacy RBM Lectures
  • 1. (Legacy) Restricted Boltzmann Machine Theory.mp4 (14.4 MB)
  • 1. (Legacy) Restricted Boltzmann Machine Theory.vtt (10.4 KB)
  • 2. (Legacy) Deriving Conditional Probabilities from Joint Probability.mp4 (9.4 MB)
  • 2. (Legacy) Deriving Conditional Probabilities from Joint Probability.vtt (5.7 KB)
  • 3. (Legacy) Contrastive Divergence for RBM Training.mp4 (4.8 MB)
  • 3. (Legacy) Contrastive Divergence for RBM Training.vtt (3.0 KB)
  • 4. (Legacy) How to derive the free energy formula.mp4 (10.9 MB)
  • 4. (Legacy) How to derive the free energy formula.vtt (5.6 KB)
12. Appendix
  • 1. What is the Appendix.mp4 (5.5 MB)
  • 1. What is the Appendix.vtt (3.3 KB)
  • 10. Python 2 vs Python 3.mp4 (7.8 MB)
  • 10. Python 2 vs Python 3.vtt (5.4 KB)
  • 11. Is Theano Dead.mp4 (17.8 MB)
  • 11. Is Theano Dead.vtt (11.3 KB)
  • 12. What order should I take your courses in (part 1).mp4 (29.3 MB)
  • 12. What order should I take your courses in (part 1).vtt (14.1 KB)
  • 13. What order should I take your courses in (part 2).mp4 (37.6 MB)
  • 13. What order should I take your courses in (part 2).vtt (20.2 KB)
  • 2. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 (4.0 MB)
  • 2. BONUS Where to get Udemy coupons and FREE deep learning material.vtt (3.0 KB)
  • 3. Windows-Focused Environment Setup 2018.mp4 (186.4 MB)
  • 3. Windows-Focused Environment Setup 2018.vtt (17.4 KB)
  • 4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 (43.9 MB)
  • 4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt (12.4 KB)
  • 5. How to Code by Yourself (part 1).mp4 (24.5 MB)
  • 5. How to Code by Yourself (part 1).vtt (19.8 KB)
  • 6. How to Code by Yourself (part 2).mp4 (14.8 MB)
  • 6. How to Code by Yourself (part 2).vtt (11.6 KB)
  • 7. How to Succeed in this Course (Long Version).mp4 (18.3 MB)
  • 7. How to Succeed in this Course (Long Version).vtt (12.8 KB)
  • 8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 (39.0 MB)
  • 8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt (27.8 KB)
  • 9. Proof that using Jupyter Notebook is the same as not using it.mp4 (78.3 MB)
  • 9. Proof that using Jupyter Notebook is the same as not using it.vtt (78.3 MB)
2. Principal Components Analysis
  • 1. What does PCA do.mp4 (27.8 MB)
  • 1. What does PCA do.vtt (5.0 KB)
  • 10. SVD (Singular Value Decomposition).mp4 (42.5 MB)
  • 10. SVD (Singular Value Decomposition).vtt (10.3 KB)
  • 2. How does PCA work.mp4 (50.9 MB)
  • 2. How does PCA work.vtt (12.4 KB)
  • 3. Why does PCA work (PCA derivation).mp4 (51.3 MB)
  • 3. Why does PCA work (PCA derivation).vtt (0.3 KB)
  • 4. PCA only rotates.mp4 (16.4 MB)
  • 4. PCA only rotates.vtt (0.3 KB)
  • 5. MNIST visualization, finding the optimal number of principal components.mp4 (9.4 MB)
  • 5. MNIST visualization, finding the optimal number of principal components.vtt (3.3 KB)
  • 6. PCA implementation.mp4 (32.1 MB)
  • 6. PCA implementation.vtt (0.3 KB)
  • 7. PCA for NLP.mp4 (16.6 MB)
  • 7. PCA for NLP.vtt (3.9 KB)
  • 8. PCA objective function.mp4 (3.7 MB)
  • 8. PCA objective function.vtt (2.3 KB)
  • 9. PCA Application Naive Bayes.mp4 (53.6 MB)
  • 9. PCA Application Naive Bayes.vtt (10.8 KB)
3. t-SNE (t-distributed Stochastic Neighbor Embedding)
  • 1. t-SNE Theory.mp4 (7.9 MB)
  • 1. t-SNE Theory.vtt (4.8 KB)
  • 2. t-SNE Visualization.mp4 (13.0 MB)
  • 2. t-SNE Visualization.vtt (4.8 KB)
  • 3. t-SNE on the Donut.mp4 (15.1 MB)
  • 3. t-SNE on the Donut.vtt (2.2 KB)
  • 4. t-SNE on XOR.mp4 (9.3 MB)
  • 4. t-SNE on XOR.vtt (3.6 KB)
  • 5. t-SNE on MNIST.mp4 (4.4 MB)
  • 5. t-SNE on MNIST.vtt (1.6 KB)
4. Autoencoders
  • 1. Autoencoders.mp4 (5.8 MB)
  • 1. Autoencoders.vtt (3.9 KB)
  • 10. Deep Autoencoder Visualization Description.mp4 (2.5 MB)
  • 10. Deep Autoencoder Visualization Description.vtt (2.0 KB)
  • 11. Deep Autoencoder Visualization in Code.mp4 (27.9 MB)
  • 11. Deep Autoencoder Visualization in Code.vtt (6.7 KB)
  • 12. An Autoencoder in 1 Line of Code.mp

Description

Unsupervised Deep Learning In Python

Theano / Tensorflow: Autoencoders, Restricted Boltzmann Machines, Deep Neural Networks, t-SNE and PCA

For More Courses Visit: https://desirecourse.com



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Udemy - Unsupervised Deep Learning In Python

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2.9 GB
seeders:9
leechers:8
Udemy - Unsupervised Deep Learning In Python

Torrent hash: FA01761607262FC54021026DCE9FB9FA6657B662