Deep Learning Hands On Artificial Neural Networks | 8EB880FE918EA42C5D71FAFB0323889C5F62DBC4

Deep Learning Hands On Artificial Neural Networks

Name	Deep Learning A-Z™ Hands-On Artificial Neural Networks	DOWNLOAD Copy Link
Total Size	3.4 GB
Total Files	155
Hash	8EB880FE918EA42C5D71FAFB0323889C5F62DBC4

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1151632 - 105 - Building a Boltzmann Machine - Step 4.mp4	67.7 MB
1151632 - 079 - Reading an Advanced SOM.mp4	64.9 MB
1151632 - 114 - Building a Boltzmann Machine - Step 13.mp4	61.4 MB
1151632 - 025 - Evaluating the ANN.mp4	58.5 MB
1151632 - 115 - Building a Boltzmann Machine - Step 14.mp4	56.7 MB
1151632 - 054 - Practical intuition.mp4	55.4 MB
1151632 - 133 - Building an AutoEncoder - Step 6.mp4	54.7 MB
1151632 - 027 - Tuning the ANN.mp4	53.2 MB
1151632 - 131 - Building an AutoEncoder - Step 4.mp4	52.0 MB
1151632 - 089 - Mega Case Study - Step 3.mp4	51.6 MB
1151632 - 047 - Building a CNN - Step 9.mp4	49.1 MB
1151632 - 053 - LSTMs.mp4	48.2 MB
1151632 - 015 - Building an ANN - Step 2.mp4	48.1 MB
1151632 - 034 - Step 4 - Full Connection.mp4	44.8 MB
1151632 - 154 - Logistic Regression Implementation - Step 5.mp4	44.5 MB
1151632 - 113 - Building a Boltzmann Machine - Step 12.mp4	43.6 MB
1151632 - 049 - Homework Solution.mp4	42.9 MB
1151632 - 032 - Step 2 - Pooling.mp4	42.2 MB
1151632 - 109 - Building a Boltzmann Machine - Step 8.mp4	41.3 MB
1151632 - 095 - Restricted Boltzmann Machine.mp4	41.2 MB
1151632 - 024 - Homework Solution.mp4	39.5 MB
1151632 - 051 - The idea behind Recurrent Neural Networks.mp4	39.1 MB
1151632 - 128 - Building an AutoEncoder - Step 1.mp4	38.5 MB
1151632 - 085 - Building a SOM - Step 3.mp4	37.8 MB
1151632 - 101 - Building a Boltzmann Machine - Introduction.mp4	35.7 MB
1151632 - 135 - Building an AutoEncoder - Step 8.mp4	35.5 MB
1151632 - 134 - Building an AutoEncoder - Step 7.mp4	35.3 MB
1151632 - 036 - Softmax & Cross-Entropy.mp4	34.8 MB
1151632 - 111 - Building a Boltzmann Machine - Step 10.mp4	34.8 MB
1151632 - 092 - Boltzmann Machine.mp4	33.5 MB
1151632 - 136 - Building an AutoEncoder - Step 9.mp4	33.1 MB
1151632 - 001 - What is Deep Learning .mp4	32.8 MB
1151632 - 108 - Building a Boltzmann Machine - Step 7.mp4	32.7 MB
1151632 - 076 - How do Self-Organizing Maps Learn (Part 1).mp4	32.6 MB
1151632 - 030 - Step 1 - Convolution Operation.mp4	32.5 MB
1151632 - 090 - Mega Case Study - Step 4.mp4	32.3 MB
1151632 - 083 - Building a SOM - Step 1.mp4	32.2 MB
1151632 - 102 - Building a Boltzmann Machine - Step 1.mp4	31.9 MB
1151632 - 058 - Building a RNN - Step 1.mp4	31.8 MB
1151632 - 018 - Building an ANN - Step 5.mp4	31.0 MB
1151632 - 005 - The Neuron.mp4	31.0 MB
1151632 - 103 - Building a Boltzmann Machine - Step 2.mp4	31.0 MB
1151632 - 096 - Contrastive Divergence.mp4	31.0 MB
1151632 - 029 - What are convolutional neural networks .mp4	30.9 MB
1151632 - 142 - Logistic Regression Intuition.mp4	30.6 MB
1151632 - 052 - The Vanishing Gradient Problem.mp4	30.4 MB
1151632 - 146 - Data Preprocessing - Step 4.mp4	30.4 MB
1151632 - 086 - Building a SOM - Step 4.mp4	30.1 MB
1151632 - 138 - Building an AutoEncoder - Step 11.mp4	29.7 MB
1151632 - 117 - Auto Encoders.mp4	29.6 MB
1151632 - 129 - Building an AutoEncoder - Step 2.mp4	29.2 MB
1151632 - 094 - Editing Wikipedia - Our Contribution to the World.mp4	28.7 MB
1151632 - 042 - Building a CNN - Step 4.mp4	28.5 MB
1151632 - 008 - How do Neural Networks learn .mp4	27.8 MB
1151632 - 104 - Building a Boltzmann Machine - Step 3.mp4	27.2 MB
1151632 - 107 - Building a Boltzmann Machine - Step 6.mp4	26.4 MB
1151632 - 075 - K-Means Clustering (Refresher).mp4	26.2 MB
1151632 - 014 - Building an ANN - Step 1.mp4	25.5 MB
1151632 - 007 - How do Neural Networks work .mp4	24.7 MB
1151632 - 147 - Data Preprocessing - Step 5.mp4	24.0 MB
1151632 - 148 - Data Preprocessing - Step 6.mp4	23.9 MB
1151632 - 112 - Building a Boltzmann Machine - Step 11.mp4	23.5 MB
1151632 - 081 - EXTRA K-means Clustering (part 3).mp4	22.9 MB
1151632 - 145 - Data Preprocessing - Step 3.mp4	22.8 MB
1151632 - 048 - Building a CNN - Step 10.mp4	21.5 MB
1151632 - 110 - Building a Boltzmann Machine - Step 9.mp4	21.4 MB
1151632 - 002 - Installing Python.mp4	21.4 MB
1151632 - 130 - Building an AutoEncoder - Step 3.mp4	21.1 MB
1151632 - 073 - How do Self-Organizing Maps Work .mp4	21.0 MB
1151632 - 026 - Improving the ANN.mp4	20.8 MB
1151632 - 084 - Building a SOM - Step 2.mp4	20.4 MB
1151632 - 039 - Building a CNN - Step 1.mp4	20.1 MB
1151632 - 068 - Building a RNN - Step 11.mp4	19.9 MB
1151632 - 077 - How do Self-Organizing Maps Learn (Part 2).mp4	19.6 MB
1151632 - 078 - Live SOM example.mp4	19.4 MB
1151632 - 009 - Gradient Descent.mp4	19.4 MB
1151632 - 093 - Energy-Based Models (EBM).mp4	19.4 MB
1151632 - 056 - Ethical Disclosure.mp4	19.2 MB
1151632 - 021 - Building an ANN - Step 8.mp4	19.1 MB
1151632 - 069 - Building a RNN - Step 12.mp4	19.1 MB
1151632 - 023 - Building an ANN - Step 10.mp4	18.3 MB
1151632 - 022 - Building an ANN - Step 9.mp4	17.7 MB
1151632 - 010 - Stochastic Gradient Descent.mp4	17.6 MB
1151632 - 013 - Business Problem Description.mp4	17.2 MB
1151632 - 144 - Data Preprocessing - Step 2.mp4	16.6 MB
1151632 - 106 - Building a Boltzmann Machine - Step 5.mp4	16.2 MB
1151632 - 070 - Homework Solution.mp4	15.7 MB
1151632 - 006 - The Activation Function.mp4	15.5 MB
1151632 - 031 - Step 1(b) - ReLU Layer.mp4	14.8 MB
1151632 - 121 - Sparse Autoencoders.mp4	14.7 MB
1151632 - 119 - Training an Auto Encoder.mp4	14.2 MB
1151632 - 088 - Mega Case Study - Step 2.mp4	14.0 MB
1151632 - 143 - Data Preprocessing - Step 1.mp4	13.9 MB
1151632 - 071 - Evaluating the RNN.mp4	13.8 MB
1151632 - 097 - Deep Belief Networks.mp4	13.2 MB
1151632 - 045 - Building a CNN - Step 7.mp4	13.2 MB
1151632 - 080 - EXTRA K-means Clustering (part 2).mp4	12.9 MB
1151632 - 150 - Logistic Regression Implementation - Step 1.mp4	12.8 MB
1151632 - 061 - Building a RNN - Step 4.mp4	12.6 MB
1151632 - 132 - Building an AutoEncoder - Step 5.mp4	12.4 MB
1151632 - 155 - Classification Template.mp4	12.3 MB
1151632 - 137 - Building an AutoEncoder - Step 10.mp4	11.8 MB
1151632 - 063 - Building a RNN - Step 6.mp4	11.7 MB
1151632 - 011 - Backpropagation.mp4	11.5 MB
1151632 - 043 - Building a CNN - Step 5.mp4	10.4 MB
1151632 - 044 - Building a CNN - Step 6.mp4	10.2 MB
1151632 - 153 - Logistic Regression Implementation - Step 4.mp4	10.1 MB
1151632 - 139 - Simple Linear Regression Intuition - Step 1.mp4	9.9 MB
1151632 - 060 - Building a RNN - Step 3.mp4	9.6 MB
1151632 - 020 - Building an ANN - Step 7.mp4	9.4 MB
1151632 - 016 - Building an ANN - Step 3.mp4	8.8 MB
1151632 - 151 - Logistic Regression Implementation - Step 2.mp4	8.5 MB
1151632 - 149 - Data Preprocessing Template.mp4	8.5 MB
1151632 - 059 - Building a RNN - Step 2.mp4	8.4 MB
1151632 - 066 - Building a RNN - Step 9.mp4	8.3 MB
1151632 - 035 - Summary.mp4	8.3 MB
1151632 - 038 - Introduction to CNNs.mp4	8.2 MB
1151632 - 065 - Building a RNN - Step 8.mp4	8.1 MB
1151632 - 120 - Overcomplete hidden layers.mp4	8.0 MB
1151632 - 055 - EXTRA LSTM Variations.mp4	7.7 MB
1151632 - 019 - Building an ANN - Step 6.mp4	7.4 MB
1151632 - 062 - Building a RNN - Step 5.mp4	7.2 MB
1151632 - 046 - Building a CNN - Step 8.mp4	7.1 MB
1151632 - 067 - Building a RNN - Step 10.mp4	7.0 MB
1151632 - 126 - How to get the dataset.mp4	6.8 MB
1151632 - 057 - How to get the dataset.mp4	6.8 MB
1151632 - 099 - How to get the dataset.mp4	6.8 MB
1151632 - 003 - How to get the dataset.mp4	6.8 MB
1151632 - 082 - How to get the dataset.mp4	6.8 MB
1151632 - 037 - How to get the dataset.mp4	6.8 MB
1151632 - 012 - How to get the dataset.mp4	6.8 MB
1151632 - 152 - Logistic Regression Implementation - Step 3.mp4	6.2 MB
1151632 - 017 - Building an ANN - Step 4.mp4	6.2 MB
1151632 - 028 - Plan of attack.mp4	6.2 MB
1151632 - 040 - Building a CNN - Step 2.mp4	6.1 MB
1151632 - 098 - Deep Boltzmann Machines.mp4	6.1 MB
1151632 - 122 - Denoising Autoencoders.mp4	6.0 MB
1151632 - 100 - Installing PyTorch.mp4	6.0 MB
1151632 - 127 - Installing PyTorch.mp4	6.0 MB
1151632 - 087 - Mega Case Study - Step 1.mp4	5.7 MB
1151632 - 140 - Simple Linear Regression Intuition - Step 2.mp4	5.6 MB
1151632 - 123 - Contractive Autoencoders.mp4	5.5 MB
1151632 - 072 - Plan of attack.mp4	5.4 MB
1151632 - 004 - Plan of Attack.mp4	5.0 MB
1151632 - 124 - Stacked Autoencoders.mp4	4.7 MB
1151632 - 050 - Plan of attack.mp4	4.4 MB
1151632 - 064 - Building a RNN - Step 7.mp4	4.4 MB
1151632 - 116 - Plan of attack.mp4	4.3 MB
1151632 - 074 - Why revisit K-Means .mp4	4.2 MB
1151632 - 091 - Plan of attack.mp4	4.0 MB
1151632 - 125 - Deep Autoencoders.mp4	3.5 MB
1151632 - 033 - Step 3 - Flattening.mp4	3.4 MB
1151632 - 118 - A Note on Biases.mp4	2.6 MB
1151632 - 041 - Building a CNN - Step 3.mp4	2.3 MB
1151632 - 141 - Multiple Linear Regression Intuition.mp4	1.9 MB
Total files 155