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种子名称:
Udemy - Unsupervised Deep Learning in Python - TUTSEM
文件类型:
视频
文件数目:
38个文件
文件大小:
556.36 MB
收录时间:
2021-5-26 13:10
已经下载:
3次
资源热度:
160
最近下载:
2024-12-19 23:22
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Udemy - Unsupervised Deep Learning in Python - TUTSEM.torrent
01 Introduction and Outline/001 Introduction and Outline.mp43.27MB
01 Introduction and Outline/002 Where does this course fit into your deep learning studies.mp45.18MB
01 Introduction and Outline/003 How to Succeed in this Course.mp49.52MB
02 Principal Components Analysis/004 What does PCA do.mp411.49MB
02 Principal Components Analysis/005 PCA derivation.mp46.66MB
02 Principal Components Analysis/006 MNIST visualization finding the optimal number of principal components.mp49.38MB
02 Principal Components Analysis/007 PCA objective function.mp43.68MB
03 t-SNE t-distributed Stochastic Neighbor Embedding/008 t-SNE Theory.mp47.9MB
03 t-SNE t-distributed Stochastic Neighbor Embedding/009 t-SNE on the Donut.mp415.1MB
03 t-SNE t-distributed Stochastic Neighbor Embedding/010 t-SNE on XOR.mp49.31MB
03 t-SNE t-distributed Stochastic Neighbor Embedding/011 t-SNE on MNIST.mp44.34MB
04 Autoencoders/012 Autoencoders.mp45.82MB
04 Autoencoders/013 Denoising Autoencoders.mp43.43MB
04 Autoencoders/014 Stacked Autoencoders.mp46.6MB
04 Autoencoders/015 Writing the autoencoder class in code Theano.mp438.51MB
04 Autoencoders/016 Testing our Autoencoder Theano.mp411.36MB
04 Autoencoders/017 Writing the deep neural network class in code Theano.mp441.96MB
04 Autoencoders/018 Autoencoder in Code Tensorflow.mp424.45MB
04 Autoencoders/019 Testing greedy layer-wise autoencoder training vs. pure backpropagation.mp418.53MB
04 Autoencoders/020 Cross Entropy vs. KL Divergence.mp47.41MB
04 Autoencoders/021 Deep Autoencoder Visualization Description.mp42.45MB
04 Autoencoders/022 Deep Autoencoder Visualization in Code.mp427.85MB
05 Restricted Boltzmann Machines/023 Restricted Boltzmann Machine Theory.mp414.38MB
05 Restricted Boltzmann Machines/024 Deriving Conditional Probabilities from Joint Probability.mp49.37MB
05 Restricted Boltzmann Machines/025 Contrastive Divergence for RBM Training.mp44.84MB
05 Restricted Boltzmann Machines/026 RBM in Code Theano with Greedy Layer-Wise Training on MNIST.mp447.76MB
05 Restricted Boltzmann Machines/027 RBM in Code Tensorflow.mp413.7MB
06 The Vanishing Gradient Problem/028 The Vanishing Gradient Problem Description.mp45.2MB
06 The Vanishing Gradient Problem/029 The Vanishing Gradient Problem Demo in Code.mp431.29MB
07 Extras Visualizing what features a neural network has learned/030 Exercises on feature visualization and interpretation.mp43.75MB
07 Extras Visualizing what features a neural network has learned/031 BONUS Where to get Udemy coupons and FREE deep learning material.mp42.23MB
07 Extras Visualizing what features a neural network has learned/032 BONUS How to derive the free energy formula.mp410.88MB
08 BONUS Application of PCA SVD to NLP Natural Language Processing/033 BONUS Application of PCA and SVD to NLP Natural Language Processing.mp43.93MB
08 BONUS Application of PCA SVD to NLP Natural Language Processing/034 BONUS Latent Semantic Analysis in Code.mp425.61MB
08 BONUS Application of PCA SVD to NLP Natural Language Processing/035 BONUS Application of t-SNE K-Means Finding Clusters of Related Words.mp425.98MB
09 Appendix/036 How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.mp443.92MB
09 Appendix/037 How to Code by Yourself part 1.mp424.53MB
09 Appendix/038 How to Code by Yourself part 2.mp414.8MB