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| [TGx]Downloaded from torrentgalaxy.to .txt |
585B |
| 0 |
72B |
| 001 Course Structure.en.srt |
1.61KB |
| 001 Course Structure.mp4 |
15.03MB |
| 002 How To Make The Most Out Of This Course.en.srt |
2.54KB |
| 002 How To Make The Most Out Of This Course.mp4 |
8.20MB |
| 003 What is Neuron.en.srt |
1.86KB |
| 003 What is Neuron.mp4 |
7.22MB |
| 004 What is Deep Learning.en.srt |
1.41KB |
| 004 What is Deep Learning.mp4 |
18.49MB |
| 005 What is ANN.en.srt |
4.38KB |
| 005 What is ANN.mp4 |
18.25MB |
| 006 What is Tensorflow and how to install it.en.srt |
2.31KB |
| 006 What is Tensorflow and how to install it.mp4 |
20.51MB |
| 007 Important note about tools in this course.en.srt |
1.76KB |
| 007 Important note about tools in this course.mp4 |
5.09MB |
| 008 Multilayer Neural Network.en.srt |
7.19KB |
| 008 Multilayer Neural Network.mp4 |
40.28MB |
| 009 Introduction to Pandas and visualization.en.srt |
11.85KB |
| 009 Introduction to Pandas and visualization.mp4 |
61.06MB |
| 010 Data Preprocessing by Pandas.en.srt |
10.29KB |
| 010 Data Preprocessing by Pandas.mp4 |
60.18MB |
| 011 (OPTIONAL) Anaconda Installation.en.srt |
2.54KB |
| 011 (OPTIONAL) Anaconda Installation.mp4 |
26.24MB |
| 012 Some Of The Important Terms In Neural Network.en.srt |
11.76KB |
| 012 Some Of The Important Terms In Neural Network.mp4 |
105.91MB |
| 013 What is activation function.en.srt |
1.50KB |
| 013 What is activation function.mp4 |
7.60MB |
| 014 What is sigmoid function.en.srt |
1.55KB |
| 014 What is sigmoid function.mp4 |
3.25MB |
| 015 What is tanh function.en.srt |
1.17KB |
| 015 What is tanh function.mp4 |
2.39MB |
| 016 What is Rectified Linear Unit function.en.srt |
875B |
| 016 What is Rectified Linear Unit function.mp4 |
2.25MB |
| 017 What is Leaky ReLU function.en.srt |
875B |
| 017 What is Leaky ReLU function.mp4 |
2.25MB |
| 018 What is The Exponential Linear Unit Function.en.srt |
853B |
| 018 What is The Exponential Linear Unit Function.mp4 |
1.86MB |
| 019 What is The Swish function.en.srt |
2.00KB |
| 019 What is The Swish function.mp4 |
3.74MB |
| 020 What is The Softmax function.en.srt |
1.27KB |
| 020 What is The Softmax function.mp4 |
2.40MB |
| 021 Activation-function.ipynb |
2.50KB |
| 021 Time to code all the activation functions.en.srt |
7.16KB |
| 021 Time to code all the activation functions.mp4 |
36.90MB |
| 022 Introduction to the project.en.srt |
1.99KB |
| 022 Introduction to the project.mp4 |
13.43MB |
| 023 ConcreteData.xlsx |
69.19KB |
| 023 Importing Data and Libraries.en.srt |
8.67KB |
| 023 Importing Data and Libraries.mp4 |
54.32MB |
| 024 Exploratory analysis.en.srt |
2.74KB |
| 024 Exploratory analysis.mp4 |
15.27MB |
| 025 Data Visualization.en.srt |
12.00KB |
| 025 Data Visualization.mp4 |
89.64MB |
| 026 Data scaling.en.srt |
7.94KB |
| 026 Data scaling.mp4 |
48.89MB |
| 027 Building Neural Network model.en.srt |
21.64KB |
| 027 Building Neural Network model.mp4 |
162.55MB |
| 028 Evaluating the model.en.srt |
5.42KB |
| 028 Evaluating the model.mp4 |
41.00MB |
| 029 Concrete-project.ipynb |
1.35MB |
| 029 Improving the model.en.srt |
23.61KB |
| 029 Improving the model.mp4 |
189.93MB |
| 030 Project Summary.en.srt |
3.62KB |
| 030 Project Summary.mp4 |
28.24MB |
| 031 Convolution Neural Network.en.srt |
7.97KB |
| 031 Convolution Neural Network.mp4 |
44.17MB |
| 032 Convolution Layers.en.srt |
4.25KB |
| 032 Convolution Layers.mp4 |
16.16MB |
| 033 Pooling Layers.en.srt |
4.15KB |
| 033 Pooling Layers.mp4 |
20.86MB |
| 034 Introduction to the project.en.srt |
787B |
| 034 Introduction to the project.mp4 |
6.40MB |
| 035 Importing library and data.en.srt |
8.51KB |
| 035 Importing library and data.mp4 |
64.62MB |
| 036 Compiling the model.en.srt |
10.62KB |
| 036 Compiling the model.mp4 |
115.58MB |
| 037 Training Neural Network.en.srt |
9.80KB |
| 037 Training Neural Network.mp4 |
92.03MB |
| 038 Results.en.srt |
5.93KB |
| 038 Results.mp4 |
43.24MB |
| 039 Cifar-10-Udemy.ipynb |
250.39KB |
| 039 Visualizing filters.en.srt |
8.93KB |
| 039 Visualizing filters.mp4 |
75.38MB |
| 040 Summary of the project.en.srt |
3.22KB |
| 040 Summary of the project.mp4 |
23.36MB |
| 041 Introduction to the project.en.srt |
2.77KB |
| 041 Introduction to the project.mp4 |
18.25MB |
| 042 Importing library and data.en.srt |
6.58KB |
| 042 Importing library and data.mp4 |
45.42MB |
| 043 Visualizing data.en.srt |
4.06KB |
| 043 Visualizing data.mp4 |
37.41MB |
| 044 Building Neural Network model.en.srt |
14.76KB |
| 044 Building Neural Network model.mp4 |
120.94MB |
| 045 Training and Testing Model.en.srt |
12.44KB |
| 045 Training and Testing Model.mp4 |
120.30MB |
| 046 Visualizing Convolutional Filters.en.srt |
5.21KB |
| 046 Visualizing Convolutional Filters.mp4 |
32.30MB |
| 047 Improving the clothing image classifier with data augmentation.en.srt |
13.66KB |
| 047 Improving the clothing image classifier with data augmentation.mp4 |
152.37MB |
| 047 Udemy-clothing-image.ipynb |
103.76KB |
| 048 Summary of the project.en.srt |
5.97KB |
| 048 Summary of the project.mp4 |
49.32MB |
| 049 Basic Introduction to RNN.en.srt |
8.00KB |
| 049 Basic Introduction to RNN.mp4 |
37.62MB |
| 050 Fully Recurrent Neural Networks and Recursive Neural Networks.en.srt |
2.09KB |
| 050 Fully Recurrent Neural Networks and Recursive Neural Networks.mp4 |
10.93MB |
| 051 Hopfield Recurrent Neural Networks and Elman Neural Networks.en.srt |
4.75KB |
| 051 Hopfield Recurrent Neural Networks and Elman Neural Networks.mp4 |
25.81MB |
| 052 Long Short-term Memory Network.en.srt |
4.40KB |
| 052 Long Short-term Memory Network.mp4 |
19.37MB |
| 053 Sentiment analysis basic concepts.en.srt |
5.86KB |
| 053 Sentiment analysis basic concepts.mp4 |
38.14MB |
| 054 Sentiment analysis techniques.en.srt |
2.27KB |
| 054 Sentiment analysis techniques.mp4 |
7.25MB |
| 055 The next challenges for sentiment analysis.en.srt |
3.23KB |
| 055 The next challenges for sentiment analysis.mp4 |
11.40MB |
| 056 Lexicon and semantics analysis.en.srt |
3.00KB |
| 056 Lexicon and semantics analysis.mp4 |
11.51MB |
| 057 Introduction to the project.en.srt |
4.30KB |
| 057 Introduction to the project.mp4 |
34.37MB |
| 058 Importing library and data.en.srt |
11.34KB |
| 058 Importing library and data.mp4 |
118.77MB |
| 059 Exploratory analysis.en.srt |
12.44KB |
| 059 Exploratory analysis.mp4 |
96.12MB |
| 060 Visualizing data.en.srt |
21.31KB |
| 060 Visualizing data.mp4 |
149.90MB |
| 061 Building RNN model.en.srt |
23.74KB |
| 061 Building RNN model.mp4 |
207.15MB |
| 062 Exploring Results.en.srt |
7.71KB |
| 062 Exploring Results.mp4 |
76.46MB |
| 062 Movie-Reviews-Udemy.ipynb |
1.80MB |
| 063 Summary of the project.en.srt |
1.95KB |
| 063 Summary of the project.mp4 |
22.73MB |
| 064 What is NLP.en.srt |
3.44KB |
| 064 What is NLP.mp4 |
15.34MB |
| 065 NLP Applications.en.srt |
4.19KB |
| 065 NLP Applications.mp4 |
21.17MB |
| 066 NLP tools Part 1.en.srt |
16.54KB |
| 066 NLP tools Part 1.mp4 |
110.46MB |
| 067 NLP tools Part 2.en.srt |
5.56KB |
| 067 NLP tools Part 2.mp4 |
37.02MB |
| 068 NLP tools Part 3.en.srt |
4.02KB |
| 068 NLP tools Part 3.mp4 |
24.92MB |
| 068 NLTK-tools.ipynb |
62.08KB |
| 069 NLP tools Part 4.en.srt |
2.26KB |
| 069 NLP tools Part 4.mp4 |
10.65MB |
| 070 Introduction to the project.en.srt |
1.09KB |
| 070 Introduction to the project.mp4 |
7.37MB |
| 071 Importing library and data.en.srt |
15.09KB |
| 071 Importing library and data.mp4 |
107.86MB |
| 072 Exploring the newsgroups data.en.srt |
7.71KB |
| 072 Exploring the newsgroups data.mp4 |
52.42MB |
| 073 Counting the occurrence of each word token.en.srt |
13.76KB |
| 073 Counting the occurrence of each word token.mp4 |
92.14MB |
| 074 Text Preprocessing.en.srt |
2.20KB |
| 074 Text Preprocessing.mp4 |
18.47MB |
| 075 Dropping Stop Words.en.srt |
2.82KB |
| 075 Dropping Stop Words.mp4 |
20.40MB |
| 076 Reducing inflectional and derivational forms of words.en.srt |
7.24KB |
| 076 Reducing inflectional and derivational forms of words.mp4 |
69.30MB |
| 077 What Is Dimensionality Reduction_.en.srt |
5.77KB |
| 077 What Is Dimensionality Reduction_.mp4 |
50.99MB |
| 078 T-SNE for Dimensionality Reduction.en.srt |
16.66KB |
| 078 T-SNE for Dimensionality Reduction.mp4 |
155.24MB |
| 078 Udemy-Newsgroup-project.ipynb |
356.28KB |
| 079 Summary of the project.en.srt |
3.19KB |
| 079 Summary of the project.mp4 |
34.42MB |
| 080 Autoencoder introduction.en.srt |
6.26KB |
| 080 Autoencoder introduction.mp4 |
47.59MB |
| 081 Principle of Autoencoder.en.srt |
5.46KB |
| 081 Principle of Autoencoder.mp4 |
39.35MB |
| 082 Importing library and data.en.srt |
6.34KB |
| 082 Importing library and data.mp4 |
57.31MB |
| 083 IMPORTANT note.html |
2.53KB |
| 084 Build autoencoder model.en.srt |
10.57KB |
| 084 Build autoencoder model.mp4 |
96.27MB |
| 085 Reconstructing the input.en.srt |
5.45KB |
| 085 Reconstructing the input.mp4 |
45.14MB |
| 086 Train the autoencoder model.en.srt |
6.59KB |
| 086 Train the autoencoder model.mp4 |
52.01MB |
| 087 Summary of the autoencoder model.en.srt |
6.20KB |
| 087 Summary of the autoencoder model.mp4 |
46.83MB |
| 088 Visualizing latent vector PART 1.en.srt |
10.73KB |
| 088 Visualizing latent vector PART 1.mp4 |
93.82MB |
| 089 Visualizing latent vector PART 2.en.srt |
8.98KB |
| 089 Visualizing latent vector PART 2.mp4 |
95.15MB |
| 090 Analysing Results.en.srt |
3.29KB |
| 090 Analysing Results.mp4 |
30.59MB |
| 090 Udemy-Autoencoder-Implementation.ipynb |
894.53KB |
| 091 Summary of the project.en.srt |
1.97KB |
| 091 Summary of the project.mp4 |
21.40MB |
| 091 Udemy-Autoencoder-Implementation.ipynb |
894.53KB |
| 092 Denoising autoencoders Implementation Part 1.en.srt |
5.36KB |
| 092 Denoising autoencoders Implementation Part 1.mp4 |
38.02MB |
| 093 Denoising autoencoders Implementation Part 2.en.srt |
4.23KB |
| 093 Denoising autoencoders Implementation Part 2.mp4 |
50.97MB |
| 094 Denoising autoencoders Implementation Part 3.en.srt |
4.71KB |
| 094 Denoising autoencoders Implementation Part 3.mp4 |
48.53MB |
| 095 Denoising autoencoders Implementation Part 4.en.srt |
4.58KB |
| 095 Denoising autoencoders Implementation Part 4.mp4 |
47.55MB |
| 096 Denoising autoencoders Implementation Part 5.en.srt |
2.96KB |
| 096 Denoising autoencoders Implementation Part 5.mp4 |
27.19MB |
| 097 Denoising autoencoders Implementation Part 6.en.srt |
9.03KB |
| 097 Denoising autoencoders Implementation Part 6.mp4 |
89.10MB |
| 097 Udemy-Denoising-autoencoders.ipynb |
105.19KB |
| 098 What is GAN.en.srt |
2.02KB |
| 098 What is GAN.mp4 |
11.41MB |
| 099 GAN Implementation Part 1.en.srt |
9.65KB |
| 099 GAN Implementation Part 1.mp4 |
80.80MB |
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53B |
| 10 |
137.29KB |
| 100 |
749.51KB |
| 100 GAN Implementation Part 2.en.srt |
5.13KB |
| 100 GAN Implementation Part 2.mp4 |
54.37MB |
| 101 |
992.20KB |
| 101 GAN Implementation Part 3.en.srt |
11.10KB |
| 101 GAN Implementation Part 3.mp4 |
116.41MB |
| 102 |
535.25KB |
| 102 GAN Implementation Part 4.en.srt |
7.15KB |
| 102 GAN Implementation Part 4.mp4 |
53.42MB |
| 103 |
797.21KB |
| 103 GAN Implement Part 5.en.srt |
6.78KB |
| 103 GAN Implement Part 5.mp4 |
66.75MB |
| 103 Udemy-GAN-Implementation.ipynb |
242.29KB |
| 104 |
587.68KB |
| 104 Deep Convolutional GAN (DCGAN) Implementation Part 1.en.srt |
10.10KB |
| 104 Deep Convolutional GAN (DCGAN) Implementation Part 1.mp4 |
72.82MB |
| 105 |
595.45KB |
| 105 Deep Convolutional GAN (DCGAN) Implementation Part 2.en.srt |
6.12KB |
| 105 Deep Convolutional GAN (DCGAN) Implementation Part 2.mp4 |
58.58MB |
| 106 |
60.99KB |
| 106 Deep Convolutional GAN (DCGAN) Implementation Part 3.en.srt |
7.47KB |
| 106 Deep Convolutional GAN (DCGAN) Implementation Part 3.mp4 |
85.51MB |
| 107 |
497.66KB |
| 107 Deep Convolutional GAN (DCGAN) Implementation Part 4.en.srt |
7.99KB |
| 107 Deep Convolutional GAN (DCGAN) Implementation Part 4.mp4 |
68.36MB |
| 107 Deep-Convolutional-GAN-DCGAN.ipynb |
63.43KB |
| 108 |
524.39KB |
| 108 Deep-Convolutional-GAN-DCGAN-1.ipynb |
204.36KB |
| 108 Summary of the project.en.srt |
2.59KB |
| 108 Summary of the project.mp4 |
27.54MB |
| 109 |
607.66KB |
| 109 Introduction to RBMs.en.srt |
1.19KB |
| 109 Introduction to RBMs.mp4 |
5.29MB |
| 11 |
601.58KB |
| 110 |
614.50KB |
| 110 BMs and RBMs.en.srt |
3.22KB |
| 110 BMs and RBMs.mp4 |
14.22MB |
| 111 |
906.35KB |
| 111 Bernoulli RBMs.en.srt |
2.58KB |
| 111 Bernoulli RBMs.mp4 |
11.11MB |
| 112 |
69.30KB |
| 112 Restricted Boltzman Machine Implementation Part 1.en.srt |
8.30KB |
| 112 Restricted Boltzman Machine Implementation Part 1.mp4 |
64.69MB |
| 113 |
363.18KB |
| 113 Restricted Boltzman Machine Implementation Part 3.en.srt |
3.68KB |
| 113 Restricted Boltzman Machine Implementation Part 3.mp4 |
26.23MB |
| 113 UDEMY-Restricted-Boltzman-Machine-Implementation.ipynb |
147.30KB |
| 114 |
815.84KB |
| 114 Restricted Boltzman Machine Implementation Part 2.en.srt |
6.03KB |
| 114 Restricted Boltzman Machine Implementation Part 2.mp4 |
46.91MB |
| 115 |
407.41KB |
| 115 Summary of the project.en.srt |
2.80KB |
| 115 Summary of the project.mp4 |
18.82MB |
| 116 |
649.01KB |
| 116 What is Deep Reinforcement Learning.en.srt |
2.69KB |
| 116 What is Deep Reinforcement Learning.mp4 |
11.49MB |
| 117 |
768.53KB |
| 117 Deep Reinforcement Learning.en.srt |
4.83KB |
| 117 Deep Reinforcement Learning.mp4 |
18.79MB |
| 118 |
802.51KB |
| 118 Reward.en.srt |
5.99KB |
| 118 Reward.mp4 |
25.97MB |
| 119 |
618.32KB |
| 119 The agent and The environment.en.srt |
2.91KB |
| 119 The agent and The environment.mp4 |
13.42MB |
| 12 |
430.46KB |
| 120 |
723.60KB |
| 120 Why Reinforcement Learning_.en.srt |
3.50KB |
| 120 Why Reinforcement Learning_.mp4 |
14.48MB |
| 121 |
931.67KB |
| 121 Introduction to Monte Carlo Method.en.srt |
3.92KB |
| 121 Introduction to Monte Carlo Method.mp4 |
21.51MB |
| 122 |
270.07KB |
| 122 Basic concepts of the Monte Carlo simulation and Monte Carlo Applications.en.srt |
5.52KB |
| 122 Basic concepts of the Monte Carlo simulation and Monte Carlo Applications.mp4 |
26.67MB |
| 123 |
763.48KB |
| 123 Introduction to the project.en.srt |
2.61KB |
| 123 Introduction to the project.mp4 |
12.94MB |
| 124 |
612.30KB |
| 124 AMZN.csv |
318.07KB |
| 124 Importing library and data.en.srt |
9.30KB |
| 124 Importing library and data.mp4 |
69.13MB |
| 125 |
625.06KB |
| 125 Exploratory analysis.en.srt |
19.65KB |
| 125 Exploratory analysis.mp4 |
108.01MB |
| 126 |
763.62KB |
| 126 Monte Carlo Simulation- Theory.en.srt |
13.07KB |
| 126 Monte Carlo Simulation- Theory.mp4 |
117.87MB |
| 127 |
772.37KB |
| 127 Monte Carlo Simulation-Implementation Part 1.en.srt |
16.42KB |
| 127 Monte Carlo Simulation-Implementation Part 1.mp4 |
134.57MB |
| 128 |
145.98KB |
| 128 Monte Carlo Simulation-Implementation Part 2.en.srt |
4.01KB |
| 128 Monte Carlo Simulation-Implementation Part 2.mp4 |
35.84MB |
| 128 Udemy-stock-price-prediction.ipynb |
132.27KB |
| 129 |
200.00KB |
| 129 Summary of the project.en.srt |
1.94KB |
| 129 Summary of the project.mp4 |
19.91MB |
| 13 |
551.23KB |
| 130 SMS Spam Detection (Available on May).html |
956B |
| 131 Extra Link.html |
1.03KB |
| 132 Thank you.en.srt |
1.69KB |
| 132 Thank you.mp4 |
23.31MB |
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| TutsNode.com.txt |
63B |