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Deep Learning A-Z™ Hands-On Artificial Neural Networks
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2017-8-6 11:09
2024-9-8 06:37
271
3.15 GB
155
磁力链接
magnet:?xt=urn:btih:8eb880fe918ea42c5d71fafb0323889c5f62dbc4
迅雷链接
thunder://QUFtYWduZXQ6P3h0PXVybjpidGloOjhlYjg4MGZlOTE4ZWE0MmM1ZDcxZmFmYjAzMjM4ODljNWY2MmRiYzRaWg==
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Deep
Learning
A-Z™
Hands-On
Artificial
Neural
Networks
文件列表
1151632 - 105 - Building a Boltzmann Machine - Step 4.mp4
64.52MB
1151632 - 079 - Reading an Advanced SOM.mp4
61.87MB
1151632 - 114 - Building a Boltzmann Machine - Step 13.mp4
58.52MB
1151632 - 025 - Evaluating the ANN.mp4
55.84MB
1151632 - 115 - Building a Boltzmann Machine - Step 14.mp4
54.1MB
1151632 - 054 - Practical intuition.mp4
52.84MB
1151632 - 133 - Building an AutoEncoder - Step 6.mp4
52.13MB
1151632 - 027 - Tuning the ANN.mp4
50.76MB
1151632 - 131 - Building an AutoEncoder - Step 4.mp4
49.56MB
1151632 - 089 - Mega Case Study - Step 3.mp4
49.25MB
1151632 - 047 - Building a CNN - Step 9.mp4
46.87MB
1151632 - 053 - LSTMs.mp4
45.96MB
1151632 - 015 - Building an ANN - Step 2.mp4
45.86MB
1151632 - 034 - Step 4 - Full Connection.mp4
42.74MB
1151632 - 154 - Logistic Regression Implementation - Step 5.mp4
42.48MB
1151632 - 113 - Building a Boltzmann Machine - Step 12.mp4
41.57MB
1151632 - 049 - Homework Solution.mp4
40.96MB
1151632 - 032 - Step 2 - Pooling.mp4
40.24MB
1151632 - 109 - Building a Boltzmann Machine - Step 8.mp4
39.4MB
1151632 - 095 - Restricted Boltzmann Machine.mp4
39.25MB
1151632 - 024 - Homework Solution.mp4
37.62MB
1151632 - 051 - The idea behind Recurrent Neural Networks.mp4
37.3MB
1151632 - 128 - Building an AutoEncoder - Step 1.mp4
36.71MB
1151632 - 085 - Building a SOM - Step 3.mp4
36.03MB
1151632 - 101 - Building a Boltzmann Machine - Introduction.mp4
34.05MB
1151632 - 135 - Building an AutoEncoder - Step 8.mp4
33.83MB
1151632 - 134 - Building an AutoEncoder - Step 7.mp4
33.7MB
1151632 - 036 - Softmax & Cross-Entropy.mp4
33.23MB
1151632 - 111 - Building a Boltzmann Machine - Step 10.mp4
33.15MB
1151632 - 092 - Boltzmann Machine.mp4
31.92MB
1151632 - 136 - Building an AutoEncoder - Step 9.mp4
31.6MB
1151632 - 001 - What is Deep Learning .mp4
31.31MB
1151632 - 108 - Building a Boltzmann Machine - Step 7.mp4
31.19MB
1151632 - 076 - How do Self-Organizing Maps Learn (Part 1).mp4
31.1MB
1151632 - 030 - Step 1 - Convolution Operation.mp4
31.02MB
1151632 - 090 - Mega Case Study - Step 4.mp4
30.84MB
1151632 - 083 - Building a SOM - Step 1.mp4
30.66MB
1151632 - 102 - Building a Boltzmann Machine - Step 1.mp4
30.45MB
1151632 - 058 - Building a RNN - Step 1.mp4
30.32MB
1151632 - 018 - Building an ANN - Step 5.mp4
29.58MB
1151632 - 005 - The Neuron.mp4
29.57MB
1151632 - 103 - Building a Boltzmann Machine - Step 2.mp4
29.57MB
1151632 - 096 - Contrastive Divergence.mp4
29.55MB
1151632 - 029 - What are convolutional neural networks .mp4
29.5MB
1151632 - 142 - Logistic Regression Intuition.mp4
29.17MB
1151632 - 052 - The Vanishing Gradient Problem.mp4
29.01MB
1151632 - 146 - Data Preprocessing - Step 4.mp4
28.95MB
1151632 - 086 - Building a SOM - Step 4.mp4
28.73MB
1151632 - 138 - Building an AutoEncoder - Step 11.mp4
28.29MB
1151632 - 117 - Auto Encoders.mp4
28.19MB
1151632 - 129 - Building an AutoEncoder - Step 2.mp4
27.81MB
1151632 - 094 - Editing Wikipedia - Our Contribution to the World.mp4
27.33MB
1151632 - 042 - Building a CNN - Step 4.mp4
27.19MB
1151632 - 008 - How do Neural Networks learn .mp4
26.55MB
1151632 - 104 - Building a Boltzmann Machine - Step 3.mp4
25.95MB
1151632 - 107 - Building a Boltzmann Machine - Step 6.mp4
25.21MB
1151632 - 075 - K-Means Clustering (Refresher).mp4
25.01MB
1151632 - 014 - Building an ANN - Step 1.mp4
24.28MB
1151632 - 007 - How do Neural Networks work .mp4
23.53MB
1151632 - 147 - Data Preprocessing - Step 5.mp4
22.89MB
1151632 - 148 - Data Preprocessing - Step 6.mp4
22.8MB
1151632 - 112 - Building a Boltzmann Machine - Step 11.mp4
22.39MB
1151632 - 081 - EXTRA K-means Clustering (part 3).mp4
21.82MB
1151632 - 145 - Data Preprocessing - Step 3.mp4
21.73MB
1151632 - 048 - Building a CNN - Step 10.mp4
20.54MB
1151632 - 110 - Building a Boltzmann Machine - Step 9.mp4
20.39MB
1151632 - 002 - Installing Python.mp4
20.38MB
1151632 - 130 - Building an AutoEncoder - Step 3.mp4
20.09MB
1151632 - 073 - How do Self-Organizing Maps Work .mp4
20.02MB
1151632 - 026 - Improving the ANN.mp4
19.83MB
1151632 - 084 - Building a SOM - Step 2.mp4
19.43MB
1151632 - 039 - Building a CNN - Step 1.mp4
19.18MB
1151632 - 068 - Building a RNN - Step 11.mp4
18.97MB
1151632 - 077 - How do Self-Organizing Maps Learn (Part 2).mp4
18.65MB
1151632 - 078 - Live SOM example.mp4
18.54MB
1151632 - 009 - Gradient Descent.mp4
18.53MB
1151632 - 093 - Energy-Based Models (EBM).mp4
18.48MB
1151632 - 056 - Ethical Disclosure.mp4
18.27MB
1151632 - 021 - Building an ANN - Step 8.mp4
18.18MB
1151632 - 069 - Building a RNN - Step 12.mp4
18.18MB
1151632 - 023 - Building an ANN - Step 10.mp4
17.43MB
1151632 - 022 - Building an ANN - Step 9.mp4
16.89MB
1151632 - 010 - Stochastic Gradient Descent.mp4
16.82MB
1151632 - 013 - Business Problem Description.mp4
16.37MB
1151632 - 144 - Data Preprocessing - Step 2.mp4
15.85MB
1151632 - 106 - Building a Boltzmann Machine - Step 5.mp4
15.44MB
1151632 - 070 - Homework Solution.mp4
15.02MB
1151632 - 006 - The Activation Function.mp4
14.75MB
1151632 - 031 - Step 1(b) - ReLU Layer.mp4
14.09MB
1151632 - 121 - Sparse Autoencoders.mp4
13.99MB
1151632 - 119 - Training an Auto Encoder.mp4
13.55MB
1151632 - 088 - Mega Case Study - Step 2.mp4
13.34MB
1151632 - 143 - Data Preprocessing - Step 1.mp4
13.25MB
1151632 - 071 - Evaluating the RNN.mp4
13.19MB
1151632 - 097 - Deep Belief Networks.mp4
12.61MB
1151632 - 045 - Building a CNN - Step 7.mp4
12.57MB
1151632 - 080 - EXTRA K-means Clustering (part 2).mp4
12.34MB
1151632 - 150 - Logistic Regression Implementation - Step 1.mp4
12.19MB
1151632 - 061 - Building a RNN - Step 4.mp4
12.02MB
1151632 - 132 - Building an AutoEncoder - Step 5.mp4
11.86MB
1151632 - 155 - Classification Template.mp4
11.71MB
1151632 - 137 - Building an AutoEncoder - Step 10.mp4
11.26MB
1151632 - 063 - Building a RNN - Step 6.mp4
11.19MB
1151632 - 011 - Backpropagation.mp4
10.92MB
1151632 - 043 - Building a CNN - Step 5.mp4
9.91MB
1151632 - 044 - Building a CNN - Step 6.mp4
9.7MB
1151632 - 153 - Logistic Regression Implementation - Step 4.mp4
9.68MB
1151632 - 139 - Simple Linear Regression Intuition - Step 1.mp4
9.47MB
1151632 - 060 - Building a RNN - Step 3.mp4
9.11MB
1151632 - 020 - Building an ANN - Step 7.mp4
8.99MB
1151632 - 016 - Building an ANN - Step 3.mp4
8.37MB
1151632 - 151 - Logistic Regression Implementation - Step 2.mp4
8.14MB
1151632 - 149 - Data Preprocessing Template.mp4
8.13MB
1151632 - 059 - Building a RNN - Step 2.mp4
7.99MB
1151632 - 066 - Building a RNN - Step 9.mp4
7.91MB
1151632 - 035 - Summary.mp4
7.91MB
1151632 - 038 - Introduction to CNNs.mp4
7.84MB
1151632 - 065 - Building a RNN - Step 8.mp4
7.73MB
1151632 - 120 - Overcomplete hidden layers.mp4
7.64MB
1151632 - 055 - EXTRA LSTM Variations.mp4
7.33MB
1151632 - 019 - Building an ANN - Step 6.mp4
7.05MB
1151632 - 062 - Building a RNN - Step 5.mp4
6.86MB
1151632 - 046 - Building a CNN - Step 8.mp4
6.79MB
1151632 - 067 - Building a RNN - Step 10.mp4
6.72MB
1151632 - 126 - How to get the dataset.mp4
6.48MB
1151632 - 057 - How to get the dataset.mp4
6.48MB
1151632 - 099 - How to get the dataset.mp4
6.48MB
1151632 - 003 - How to get the dataset.mp4
6.48MB
1151632 - 082 - How to get the dataset.mp4
6.48MB
1151632 - 037 - How to get the dataset.mp4
6.48MB
1151632 - 012 - How to get the dataset.mp4
6.48MB
1151632 - 152 - Logistic Regression Implementation - Step 3.mp4
5.96MB
1151632 - 017 - Building an ANN - Step 4.mp4
5.95MB
1151632 - 028 - Plan of attack.mp4
5.93MB
1151632 - 040 - Building a CNN - Step 2.mp4
5.85MB
1151632 - 098 - Deep Boltzmann Machines.mp4
5.85MB
1151632 - 122 - Denoising Autoencoders.mp4
5.72MB
1151632 - 100 - Installing PyTorch.mp4
5.71MB
1151632 - 127 - Installing PyTorch.mp4
5.71MB
1151632 - 087 - Mega Case Study - Step 1.mp4
5.45MB
1151632 - 140 - Simple Linear Regression Intuition - Step 2.mp4
5.37MB
1151632 - 123 - Contractive Autoencoders.mp4
5.29MB
1151632 - 072 - Plan of attack.mp4
5.19MB
1151632 - 004 - Plan of Attack.mp4
4.74MB
1151632 - 124 - Stacked Autoencoders.mp4
4.53MB
1151632 - 050 - Plan of attack.mp4
4.19MB
1151632 - 064 - Building a RNN - Step 7.mp4
4.16MB
1151632 - 116 - Plan of attack.mp4
4.06MB
1151632 - 074 - Why revisit K-Means .mp4
4.05MB
1151632 - 091 - Plan of attack.mp4
3.78MB
1151632 - 125 - Deep Autoencoders.mp4
3.31MB
1151632 - 033 - Step 3 - Flattening.mp4
3.27MB
1151632 - 118 - A Note on Biases.mp4
2.43MB
1151632 - 041 - Building a CNN - Step 3.mp4
2.23MB
1151632 - 141 - Multiple Linear Regression Intuition.mp4
1.82MB
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