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

TORRENT SUMMARY

	Status:	All the torrents in this section have been verified by our verification system
Category:	Other
Infohash	fa01761607262fc54021026dce9fb9fa6657b662
Size:	2.9 GB in 99 files
Release Date(s):	Torrent Release: 14-04-2019 by user
Swarm:	0 Seeds & 0 Peers
Vote:	No votes yet.

DESCRIPTION

Unsupervised Deep Learning In Python

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

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FILE LIST

Filename		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	26.4 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	18.9 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	11.7 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	93.4 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	81.5 MB
	10. Basics Review/3. (Review) Tensorflow Basics.vtt	5.1 KB
	10. Basics Review/4. (Review) Tensorflow Neural Network in Code.mp4	97.4 MB
	10. Basics Review/4. (Review) Tensorflow Neural Network in Code.vtt	4.8 KB
	10. Basics Review/5. (Review) Keras Basics.mp4	27.6 MB
	10. Basics Review/5. (Review) Keras Basics.vtt	8 KB
	10. Basics Review/6. (Review) Keras in Code pt 1.mp4	66.2 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	38.7 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	14.4 MB
	11. Optional - Legacy RBM Lectures/1. (Legacy) Restricted Boltzmann Machine Theory.vtt	10.4 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 KB
	11. Optional - Legacy RBM Lectures/4. (Legacy) How to derive the free energy formula.mp4	10.9 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	17.8 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	29.3 MB
	12. Appendix/12. What order should I take your courses in (part 1).vtt	14.1 KB
	12. Appendix/13. What order should I take your courses in (part 2).mp4	37.6 MB
	12. Appendix/13. What order should I take your courses in (part 2).vtt	20.2 KB
	12. Appendix/2. BONUS Where to get Udemy coupons and FREE deep learning material.mp4	4 MB
	12. Appendix/2. BONUS Where to get Udemy coupons and FREE deep learning material.vtt	3 KB
	12. Appendix/3. Windows-Focused Environment Setup 2018.mp4	186.4 MB
	12. Appendix/3. Windows-Focused Environment Setup 2018.vtt	17.4 KB
	12. Appendix/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4	43.9 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	24.5 MB
	12. Appendix/5. How to Code by Yourself (part 1).vtt	19.8 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	11.6 KB
	12. Appendix/7. How to Succeed in this Course (Long Version).mp4	18.3 MB
	12. Appendix/7. How to Succeed in this Course (Long Version).vtt	12.8 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	27.8 KB
	12. Appendix/9. Proof that using Jupyter Notebook is the same as not using it.mp4	78.3 MB
	12. Appendix/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
	2. Principal Components Analysis/1. What does PCA do.vtt	5 KB
	2. Principal Components Analysis/10. SVD (Singular Value Decomposition).mp4	42.5 MB
	2. Principal Components Analysis/10. SVD (Singular Value Decomposition).vtt	10.3 KB
	2. Principal Components Analysis/2. How does PCA work.mp4	50.9 MB
	2. Principal Components Analysis/2. How does PCA work.vtt	12.4 KB
	2. Principal Components Analysis/3. Why does PCA work (PCA derivation).mp4	51.3 MB
	2. Principal Components Analysis/3. Why does PCA work (PCA derivation).vtt	351 B
	2. Principal Components Analysis/4. PCA only rotates.mp4	16.4 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	32.1 MB
	2. Principal Components Analysis/6. PCA implementation.vtt	351 B
	2. Principal Components Analysis/7. PCA for NLP.mp4	16.6 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	53.6 MB
	2. Principal Components Analysis/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
	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	15.1 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 KB
	4. Autoencoders/11. Deep Autoencoder Visualization in Code.mp4	27.9 MB
	4. Autoencoders/11. Deep Autoencoder Visualization in Code.vtt	6.7 KB
	4. Autoencoders/12. An Autoencoder in 1 Line of Code.mp4	24.9 MB
	4. Autoencoders/12. An Autoencoder in 1 Line of Code.vtt	5.1 KB
	4. Autoencoders/2. Denoising Autoencoders.mp4	3.4 MB

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