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585б |
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72б |
| 001 Course Structure.en.srt |
1.61Кб |
| 001 Course Structure.mp4 |
15.03Мб |
| 002 How To Make The Most Out Of This Course.en.srt |
2.54Кб |
| 002 How To Make The Most Out Of This Course.mp4 |
8.20Мб |
| 003 What is Neuron.en.srt |
1.86Кб |
| 003 What is Neuron.mp4 |
7.22Мб |
| 004 What is Deep Learning.en.srt |
1.41Кб |
| 004 What is Deep Learning.mp4 |
18.49Мб |
| 005 What is ANN.en.srt |
4.38Кб |
| 005 What is ANN.mp4 |
18.25Мб |
| 006 What is Tensorflow and how to install it.en.srt |
2.31Кб |
| 006 What is Tensorflow and how to install it.mp4 |
20.51Мб |
| 007 Important note about tools in this course.en.srt |
1.76Кб |
| 007 Important note about tools in this course.mp4 |
5.09Мб |
| 008 Multilayer Neural Network.en.srt |
7.19Кб |
| 008 Multilayer Neural Network.mp4 |
40.28Мб |
| 009 Introduction to Pandas and visualization.en.srt |
11.85Кб |
| 009 Introduction to Pandas and visualization.mp4 |
61.06Мб |
| 010 Data Preprocessing by Pandas.en.srt |
10.29Кб |
| 010 Data Preprocessing by Pandas.mp4 |
60.18Мб |
| 011 (OPTIONAL) Anaconda Installation.en.srt |
2.54Кб |
| 011 (OPTIONAL) Anaconda Installation.mp4 |
26.24Мб |
| 012 Some Of The Important Terms In Neural Network.en.srt |
11.76Кб |
| 012 Some Of The Important Terms In Neural Network.mp4 |
105.91Мб |
| 013 What is activation function.en.srt |
1.50Кб |
| 013 What is activation function.mp4 |
7.60Мб |
| 014 What is sigmoid function.en.srt |
1.55Кб |
| 014 What is sigmoid function.mp4 |
3.25Мб |
| 015 What is tanh function.en.srt |
1.17Кб |
| 015 What is tanh function.mp4 |
2.39Мб |
| 016 What is Rectified Linear Unit function.en.srt |
875б |
| 016 What is Rectified Linear Unit function.mp4 |
2.25Мб |
| 017 What is Leaky ReLU function.en.srt |
875б |
| 017 What is Leaky ReLU function.mp4 |
2.25Мб |
| 018 What is The Exponential Linear Unit Function.en.srt |
853б |
| 018 What is The Exponential Linear Unit Function.mp4 |
1.86Мб |
| 019 What is The Swish function.en.srt |
2.00Кб |
| 019 What is The Swish function.mp4 |
3.74Мб |
| 020 What is The Softmax function.en.srt |
1.27Кб |
| 020 What is The Softmax function.mp4 |
2.40Мб |
| 021 Activation-function.ipynb |
2.50Кб |
| 021 Time to code all the activation functions.en.srt |
7.16Кб |
| 021 Time to code all the activation functions.mp4 |
36.90Мб |
| 022 Introduction to the project.en.srt |
1.99Кб |
| 022 Introduction to the project.mp4 |
13.43Мб |
| 023 ConcreteData.xlsx |
69.19Кб |
| 023 Importing Data and Libraries.en.srt |
8.67Кб |
| 023 Importing Data and Libraries.mp4 |
54.32Мб |
| 024 Exploratory analysis.en.srt |
2.74Кб |
| 024 Exploratory analysis.mp4 |
15.27Мб |
| 025 Data Visualization.en.srt |
12.00Кб |
| 025 Data Visualization.mp4 |
89.64Мб |
| 026 Data scaling.en.srt |
7.94Кб |
| 026 Data scaling.mp4 |
48.89Мб |
| 027 Building Neural Network model.en.srt |
21.64Кб |
| 027 Building Neural Network model.mp4 |
162.55Мб |
| 028 Evaluating the model.en.srt |
5.42Кб |
| 028 Evaluating the model.mp4 |
41.00Мб |
| 029 Concrete-project.ipynb |
1.35Мб |
| 029 Improving the model.en.srt |
23.61Кб |
| 029 Improving the model.mp4 |
189.93Мб |
| 030 Project Summary.en.srt |
3.62Кб |
| 030 Project Summary.mp4 |
28.24Мб |
| 031 Convolution Neural Network.en.srt |
7.97Кб |
| 031 Convolution Neural Network.mp4 |
44.17Мб |
| 032 Convolution Layers.en.srt |
4.25Кб |
| 032 Convolution Layers.mp4 |
16.16Мб |
| 033 Pooling Layers.en.srt |
4.15Кб |
| 033 Pooling Layers.mp4 |
20.86Мб |
| 034 Introduction to the project.en.srt |
787б |
| 034 Introduction to the project.mp4 |
6.40Мб |
| 035 Importing library and data.en.srt |
8.51Кб |
| 035 Importing library and data.mp4 |
64.62Мб |
| 036 Compiling the model.en.srt |
10.62Кб |
| 036 Compiling the model.mp4 |
115.58Мб |
| 037 Training Neural Network.en.srt |
9.80Кб |
| 037 Training Neural Network.mp4 |
92.03Мб |
| 038 Results.en.srt |
5.93Кб |
| 038 Results.mp4 |
43.24Мб |
| 039 Cifar-10-Udemy.ipynb |
250.39Кб |
| 039 Visualizing filters.en.srt |
8.93Кб |
| 039 Visualizing filters.mp4 |
75.38Мб |
| 040 Summary of the project.en.srt |
3.22Кб |
| 040 Summary of the project.mp4 |
23.36Мб |
| 041 Introduction to the project.en.srt |
2.77Кб |
| 041 Introduction to the project.mp4 |
18.25Мб |
| 042 Importing library and data.en.srt |
6.58Кб |
| 042 Importing library and data.mp4 |
45.42Мб |
| 043 Visualizing data.en.srt |
4.06Кб |
| 043 Visualizing data.mp4 |
37.41Мб |
| 044 Building Neural Network model.en.srt |
14.76Кб |
| 044 Building Neural Network model.mp4 |
120.94Мб |
| 045 Training and Testing Model.en.srt |
12.44Кб |
| 045 Training and Testing Model.mp4 |
120.30Мб |
| 046 Visualizing Convolutional Filters.en.srt |
5.21Кб |
| 046 Visualizing Convolutional Filters.mp4 |
32.30Мб |
| 047 Improving the clothing image classifier with data augmentation.en.srt |
13.66Кб |
| 047 Improving the clothing image classifier with data augmentation.mp4 |
152.37Мб |
| 047 Udemy-clothing-image.ipynb |
103.76Кб |
| 048 Summary of the project.en.srt |
5.97Кб |
| 048 Summary of the project.mp4 |
49.32Мб |
| 049 Basic Introduction to RNN.en.srt |
8.00Кб |
| 049 Basic Introduction to RNN.mp4 |
37.62Мб |
| 050 Fully Recurrent Neural Networks and Recursive Neural Networks.en.srt |
2.09Кб |
| 050 Fully Recurrent Neural Networks and Recursive Neural Networks.mp4 |
10.93Мб |
| 051 Hopfield Recurrent Neural Networks and Elman Neural Networks.en.srt |
4.75Кб |
| 051 Hopfield Recurrent Neural Networks and Elman Neural Networks.mp4 |
25.81Мб |
| 052 Long Short-term Memory Network.en.srt |
4.40Кб |
| 052 Long Short-term Memory Network.mp4 |
19.37Мб |
| 053 Sentiment analysis basic concepts.en.srt |
5.86Кб |
| 053 Sentiment analysis basic concepts.mp4 |
38.14Мб |
| 054 Sentiment analysis techniques.en.srt |
2.27Кб |
| 054 Sentiment analysis techniques.mp4 |
7.25Мб |
| 055 The next challenges for sentiment analysis.en.srt |
3.23Кб |
| 055 The next challenges for sentiment analysis.mp4 |
11.40Мб |
| 056 Lexicon and semantics analysis.en.srt |
3.00Кб |
| 056 Lexicon and semantics analysis.mp4 |
11.51Мб |
| 057 Introduction to the project.en.srt |
4.30Кб |
| 057 Introduction to the project.mp4 |
34.37Мб |
| 058 Importing library and data.en.srt |
11.34Кб |
| 058 Importing library and data.mp4 |
118.77Мб |
| 059 Exploratory analysis.en.srt |
12.44Кб |
| 059 Exploratory analysis.mp4 |
96.12Мб |
| 060 Visualizing data.en.srt |
21.31Кб |
| 060 Visualizing data.mp4 |
149.90Мб |
| 061 Building RNN model.en.srt |
23.74Кб |
| 061 Building RNN model.mp4 |
207.15Мб |
| 062 Exploring Results.en.srt |
7.71Кб |
| 062 Exploring Results.mp4 |
76.46Мб |
| 062 Movie-Reviews-Udemy.ipynb |
1.80Мб |
| 063 Summary of the project.en.srt |
1.95Кб |
| 063 Summary of the project.mp4 |
22.73Мб |
| 064 What is NLP.en.srt |
3.44Кб |
| 064 What is NLP.mp4 |
15.34Мб |
| 065 NLP Applications.en.srt |
4.19Кб |
| 065 NLP Applications.mp4 |
21.17Мб |
| 066 NLP tools Part 1.en.srt |
16.54Кб |
| 066 NLP tools Part 1.mp4 |
110.46Мб |
| 067 NLP tools Part 2.en.srt |
5.56Кб |
| 067 NLP tools Part 2.mp4 |
37.02Мб |
| 068 NLP tools Part 3.en.srt |
4.02Кб |
| 068 NLP tools Part 3.mp4 |
24.92Мб |
| 068 NLTK-tools.ipynb |
62.08Кб |
| 069 NLP tools Part 4.en.srt |
2.26Кб |
| 069 NLP tools Part 4.mp4 |
10.65Мб |
| 070 Introduction to the project.en.srt |
1.09Кб |
| 070 Introduction to the project.mp4 |
7.37Мб |
| 071 Importing library and data.en.srt |
15.09Кб |
| 071 Importing library and data.mp4 |
107.86Мб |
| 072 Exploring the newsgroups data.en.srt |
7.71Кб |
| 072 Exploring the newsgroups data.mp4 |
52.42Мб |
| 073 Counting the occurrence of each word token.en.srt |
13.76Кб |
| 073 Counting the occurrence of each word token.mp4 |
92.14Мб |
| 074 Text Preprocessing.en.srt |
2.20Кб |
| 074 Text Preprocessing.mp4 |
18.47Мб |
| 075 Dropping Stop Words.en.srt |
2.82Кб |
| 075 Dropping Stop Words.mp4 |
20.40Мб |
| 076 Reducing inflectional and derivational forms of words.en.srt |
7.24Кб |
| 076 Reducing inflectional and derivational forms of words.mp4 |
69.30Мб |
| 077 What Is Dimensionality Reduction_.en.srt |
5.77Кб |
| 077 What Is Dimensionality Reduction_.mp4 |
50.99Мб |
| 078 T-SNE for Dimensionality Reduction.en.srt |
16.66Кб |
| 078 T-SNE for Dimensionality Reduction.mp4 |
155.24Мб |
| 078 Udemy-Newsgroup-project.ipynb |
356.28Кб |
| 079 Summary of the project.en.srt |
3.19Кб |
| 079 Summary of the project.mp4 |
34.42Мб |
| 080 Autoencoder introduction.en.srt |
6.26Кб |
| 080 Autoencoder introduction.mp4 |
47.59Мб |
| 081 Principle of Autoencoder.en.srt |
5.46Кб |
| 081 Principle of Autoencoder.mp4 |
39.35Мб |
| 082 Importing library and data.en.srt |
6.34Кб |
| 082 Importing library and data.mp4 |
57.31Мб |
| 083 IMPORTANT note.html |
2.53Кб |
| 084 Build autoencoder model.en.srt |
10.57Кб |
| 084 Build autoencoder model.mp4 |
96.27Мб |
| 085 Reconstructing the input.en.srt |
5.45Кб |
| 085 Reconstructing the input.mp4 |
45.14Мб |
| 086 Train the autoencoder model.en.srt |
6.59Кб |
| 086 Train the autoencoder model.mp4 |
52.01Мб |
| 087 Summary of the autoencoder model.en.srt |
6.20Кб |
| 087 Summary of the autoencoder model.mp4 |
46.83Мб |
| 088 Visualizing latent vector PART 1.en.srt |
10.73Кб |
| 088 Visualizing latent vector PART 1.mp4 |
93.82Мб |
| 089 Visualizing latent vector PART 2.en.srt |
8.98Кб |
| 089 Visualizing latent vector PART 2.mp4 |
95.15Мб |
| 090 Analysing Results.en.srt |
3.29Кб |
| 090 Analysing Results.mp4 |
30.59Мб |
| 090 Udemy-Autoencoder-Implementation.ipynb |
894.53Кб |
| 091 Summary of the project.en.srt |
1.97Кб |
| 091 Summary of the project.mp4 |
21.40Мб |
| 091 Udemy-Autoencoder-Implementation.ipynb |
894.53Кб |
| 092 Denoising autoencoders Implementation Part 1.en.srt |
5.36Кб |
| 092 Denoising autoencoders Implementation Part 1.mp4 |
38.02Мб |
| 093 Denoising autoencoders Implementation Part 2.en.srt |
4.23Кб |
| 093 Denoising autoencoders Implementation Part 2.mp4 |
50.97Мб |
| 094 Denoising autoencoders Implementation Part 3.en.srt |
4.71Кб |
| 094 Denoising autoencoders Implementation Part 3.mp4 |
48.53Мб |
| 095 Denoising autoencoders Implementation Part 4.en.srt |
4.58Кб |
| 095 Denoising autoencoders Implementation Part 4.mp4 |
47.55Мб |
| 096 Denoising autoencoders Implementation Part 5.en.srt |
2.96Кб |
| 096 Denoising autoencoders Implementation Part 5.mp4 |
27.19Мб |
| 097 Denoising autoencoders Implementation Part 6.en.srt |
9.03Кб |
| 097 Denoising autoencoders Implementation Part 6.mp4 |
89.10Мб |
| 097 Udemy-Denoising-autoencoders.ipynb |
105.19Кб |
| 098 What is GAN.en.srt |
2.02Кб |
| 098 What is GAN.mp4 |
11.41Мб |
| 099 GAN Implementation Part 1.en.srt |
9.65Кб |
| 099 GAN Implementation Part 1.mp4 |
80.80Мб |
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| 100 GAN Implementation Part 2.en.srt |
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| 100 GAN Implementation Part 2.mp4 |
54.37Мб |
| 101 |
992.20Кб |
| 101 GAN Implementation Part 3.en.srt |
11.10Кб |
| 101 GAN Implementation Part 3.mp4 |
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| 102 |
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| 102 GAN Implementation Part 4.en.srt |
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| 102 GAN Implementation Part 4.mp4 |
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| 103 |
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| 103 GAN Implement Part 5.en.srt |
6.78Кб |
| 103 GAN Implement Part 5.mp4 |
66.75Мб |
| 103 Udemy-GAN-Implementation.ipynb |
242.29Кб |
| 104 |
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| 104 Deep Convolutional GAN (DCGAN) Implementation Part 1.en.srt |
10.10Кб |
| 104 Deep Convolutional GAN (DCGAN) Implementation Part 1.mp4 |
72.82Мб |
| 105 |
595.45Кб |
| 105 Deep Convolutional GAN (DCGAN) Implementation Part 2.en.srt |
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| 105 Deep Convolutional GAN (DCGAN) Implementation Part 2.mp4 |
58.58Мб |
| 106 |
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| 106 Deep Convolutional GAN (DCGAN) Implementation Part 3.en.srt |
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| 106 Deep Convolutional GAN (DCGAN) Implementation Part 3.mp4 |
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| 107 |
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| 107 Deep Convolutional GAN (DCGAN) Implementation Part 4.en.srt |
7.99Кб |
| 107 Deep Convolutional GAN (DCGAN) Implementation Part 4.mp4 |
68.36Мб |
| 107 Deep-Convolutional-GAN-DCGAN.ipynb |
63.43Кб |
| 108 |
524.39Кб |
| 108 Deep-Convolutional-GAN-DCGAN-1.ipynb |
204.36Кб |
| 108 Summary of the project.en.srt |
2.59Кб |
| 108 Summary of the project.mp4 |
27.54Мб |
| 109 |
607.66Кб |
| 109 Introduction to RBMs.en.srt |
1.19Кб |
| 109 Introduction to RBMs.mp4 |
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| 110 |
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| 110 BMs and RBMs.en.srt |
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| 110 BMs and RBMs.mp4 |
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| 111 |
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| 111 Bernoulli RBMs.en.srt |
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| 111 Bernoulli RBMs.mp4 |
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| 112 |
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| 112 Restricted Boltzman Machine Implementation Part 1.en.srt |
8.30Кб |
| 112 Restricted Boltzman Machine Implementation Part 1.mp4 |
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| 113 |
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| 113 Restricted Boltzman Machine Implementation Part 3.en.srt |
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| 113 Restricted Boltzman Machine Implementation Part 3.mp4 |
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| 113 UDEMY-Restricted-Boltzman-Machine-Implementation.ipynb |
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| 114 |
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| 114 Restricted Boltzman Machine Implementation Part 2.en.srt |
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| 114 Restricted Boltzman Machine Implementation Part 2.mp4 |
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| 115 |
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| 115 Summary of the project.en.srt |
2.80Кб |
| 115 Summary of the project.mp4 |
18.82Мб |
| 116 |
649.01Кб |
| 116 What is Deep Reinforcement Learning.en.srt |
2.69Кб |
| 116 What is Deep Reinforcement Learning.mp4 |
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| 117 |
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| 117 Deep Reinforcement Learning.en.srt |
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| 117 Deep Reinforcement Learning.mp4 |
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| 118 |
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| 118 Reward.en.srt |
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| 118 Reward.mp4 |
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| 119 |
618.32Кб |
| 119 The agent and The environment.en.srt |
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| 119 The agent and The environment.mp4 |
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| 120 |
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| 120 Why Reinforcement Learning_.en.srt |
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| 120 Why Reinforcement Learning_.mp4 |
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| 121 |
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| 121 Introduction to Monte Carlo Method.en.srt |
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| 121 Introduction to Monte Carlo Method.mp4 |
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| 122 |
270.07Кб |
| 122 Basic concepts of the Monte Carlo simulation and Monte Carlo Applications.en.srt |
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| 122 Basic concepts of the Monte Carlo simulation and Monte Carlo Applications.mp4 |
26.67Мб |
| 123 |
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| 123 Introduction to the project.en.srt |
2.61Кб |
| 123 Introduction to the project.mp4 |
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| 124 |
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| 124 AMZN.csv |
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| 124 Importing library and data.en.srt |
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| 124 Importing library and data.mp4 |
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| 125 |
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| 125 Exploratory analysis.en.srt |
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| 125 Exploratory analysis.mp4 |
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| 126 Monte Carlo Simulation- Theory.en.srt |
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| 126 Monte Carlo Simulation- Theory.mp4 |
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| 127 Monte Carlo Simulation-Implementation Part 1.en.srt |
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| 127 Monte Carlo Simulation-Implementation Part 1.mp4 |
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| 128 Monte Carlo Simulation-Implementation Part 2.en.srt |
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| 128 Monte Carlo Simulation-Implementation Part 2.mp4 |
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| 128 Udemy-stock-price-prediction.ipynb |
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| 129 Summary of the project.en.srt |
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| 129 Summary of the project.mp4 |
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| 130 SMS Spam Detection (Available on May).html |
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| 131 Extra Link.html |
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| 132 Thank you.en.srt |
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| 132 Thank you.mp4 |
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| 90 |
88.70Кб |
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649.75Кб |
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181.32Кб |
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214.02Кб |
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518.94Кб |
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544.52Кб |
| 96 |
766.12Кб |
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769.92Кб |
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855.41Кб |
| 99 |
677.29Кб |
| TutsNode.com.txt |
63б |