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[FreeCourseSite com] Udemy - Artificial Intelligence Masterclass
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Name:[FreeCourseSite com] Udemy - Artificial Intelligence Masterclass
Infohash: 6B7678D03113B9CE29EE3CA1E8846987CD13E4DE
Total Size: 6.17 GB
Magnet: Magnet Download
Seeds: 1
Leechers: 0
Stream: Watch Full Movie @ Movie4u
Last Updated: 2024-10-27 02:12:45 (Update Now)
Torrent added: 2019-03-30 06:30:24
Torrent Files List
1. Introduction (Size: 6.17 GB) (Files: 158)
1. Introduction
1. Updates on Udemy Reviews.mp4
46.04 MB1. Updates on Udemy Reviews.vtt
3.05 KB2. Introduction + Course Structure + Demo.mp4
156.76 MB2. Introduction + Course Structure + Demo.vtt
19.92 KB3. Your Three Best Resources.mp4
143.26 MB3. Your Three Best Resources.vtt
12.23 KB4. Download the Resources here.html
3.04 KB5. Meet your instructors!.html
0.71 KB10. Step 9 - Reinforcement Learning
1. Welcome to Step 9 - Reinforcement Learning.html
0.41 KB2. What is Reinforcement Learning.mp4
68.60 MB2. What is Reinforcement Learning.vtt
16.10 KB3. A Pseudo Implementation of Reinforcement Learning for the Full World Model.mp4
154.25 MB3. A Pseudo Implementation of Reinforcement Learning for the Full World Model.vtt
24.55 KB4. Full Code Section.html
0.38 KB11. Step 10 - Deep NeuroEvolution
1. Welcome to Step 10 - Deep NeuroEvolution.html
1.22 KB2. Deep NeuroEvolution.mp4
108.84 MB2. Deep NeuroEvolution.vtt
13.84 KB3. Evolution Strategies.mp4
119.43 MB3. Evolution Strategies.vtt
11.88 KB4. Genetic Algorithms.mp4
149.11 MB4. Genetic Algorithms.vtt
15.43 KB5. Covariance-Matrix Adaptation Evolution Strategy (CMA-ES).mp4
144.07 MB5. Covariance-Matrix Adaptation Evolution Strategy (CMA-ES).vtt
15.76 KB6. Parameter-Exploring Policy Gradients (PEPG).mp4
143.91 MB6. Parameter-Exploring Policy Gradients (PEPG).vtt
15.06 KB7. OpenAI Evolution Strategy.mp4
108.10 MB7. OpenAI Evolution Strategy.vtt
9.74 KB12. The Final Run
1. The Whole Implementation.mp4
191.62 MB1. The Whole Implementation.vtt
25.70 KB2. Download the whole AI Masterclass folder here.html
1.02 KB2.1 AI_Masterclass.zip.zip
17.06 MB3. Installing the required packages.mp4
158.71 MB3. Installing the required packages.vtt
15.06 KB4. The Final Race Human Intelligence vs. Artificial Intelligence.mp4
125.10 MB4. The Final Race Human Intelligence vs. Artificial Intelligence.vtt
14.03 KB2. Step 1 - Artificial Neural Network
1. Welcome to Step 1 - Artificial Neural Network.html
0.59 KB2. Plan of Attack.mp4
11.87 MB2. Plan of Attack.vtt
3.47 KB3. The Neuron.mp4
98.79 MB3. The Neuron.vtt
21.98 KB4. The Activation Function.mp4
45.36 MB4. The Activation Function.vtt
10.53 KB5. How do Neural Networks work.mp4
81.95 MB5. How do Neural Networks work.vtt
17.31 KB6. How do Neural Networks learn.mp4
112.12 MB6. How do Neural Networks learn.vtt
17.02 KB7. Gradient Descent.mp4
60.63 MB7. Gradient Descent.vtt
12.67 KB8. Stochastic Gradient Descent.mp4
67.30 MB8. Stochastic Gradient Descent.vtt
11.24 KB9. Backpropagation.mp4
43.14 MB9. Backpropagation.vtt
6.73 KB3. Step 2 - Convolutional Neural Network
1. Welcome to Step 2 - Convolutional Neural Network.html
0.42 KB10. Softmax & Cross-Entropy.mp4
117.97 MB10. Softmax & Cross-Entropy.vtt
23.04 KB2. Plan of Attack.mp4
15.82 MB2. Plan of Attack.vtt
4.80 KB3. What are Convolutional Neural Networks.mp4
107.98 MB3. What are Convolutional Neural Networks.vtt
19.87 KB4. Step 1 - The Convolution Operation.mp4
97.94 MB4. Step 1 - The Convolution Operation.vtt
21.45 KB5. Step 1 Bis - The ReLU Layer.mp4
53.45 MB5. Step 1 Bis - The ReLU Layer.vtt
8.45 KB6. Step 2 - Pooling.mp4
140.18 MB6. Step 2 - Pooling.vtt
19.09 KB7. Step 3 - Flattening.mp4
7.95 MB7. Step 3 - Flattening.vtt
2.33 KB8. Step 4 - Full Connection.mp4
194.27 MB8. Step 4 - Full Connection.vtt
26.11 KB9. Summary.mp4
30.33 MB9. Summary.vtt
5.68 KB4. Step 3 - AutoEncoder
1. Welcome to Step 3 - AutoEncoder.html
0.41 KB10. Stacked AutoEncoders.mp4
16.45 MB10. Stacked AutoEncoders.vtt
14.39 MB11. Deep AutoEncoders.mp4
11.96 MB11. Deep AutoEncoders.vtt
2.49 KB2. Plan of Attack.mp4
11.85 MB2. Plan of Attack.vtt
2.84 KB3. What are AutoEncoders.mp4
94.62 MB3. What are AutoEncoders.vtt
14.56 KB4. A Note on Biases.mp4
8.62 MB4. A Note on Biases.vtt
1.92 KB5. Training an AutoEncoder.mp4
50.31 MB5. Training an AutoEncoder.vtt
8.65 KB6. Overcomplete Hidden Layers.mp4
28.07 MB6. Overcomplete Hidden Layers.vtt
4.98 KB7. Sparse AutoEncoders.mp4
57.46 MB7. Sparse AutoEncoders.vtt
8.16 KB8. Denoising AutoEncoders.mp4
24.11 MB8. Denoising AutoEncoders.vtt
3.19 KB9. Contractive AutoEncoders.mp4
20.56 MB9. Contractive AutoEncoders.vtt
3.29 KB5. Step 4 - Variational AutoEncoder
1. Welcome to Step 4 - Variational AutoEncoder.html
0.41 KB2. Introduction to the VAE.mp4
103.69 MB2. Introduction to the VAE.vtt
10.00 KB3. Variational AutoEncoders.mp4
26.32 MB3. Variational AutoEncoders.vtt
5.71 KB4. Reparameterization Trick.mp4
26.41 MB4. Reparameterization Trick.vtt
6.16 KB6. Step 5 - Implementing the CNN-VAE
1. Welcome to Step 5 - Implementing the CNN-VAE.html
2.30 KB2. Introduction to Step 5.mp4
58.86 MB2. Introduction to Step 5.vtt
9.81 KB3. Initializing all the parameters and variables of the CNN-VAE class.mp4
71.72 MB3. Initializing all the parameters and variables of the CNN-VAE class.vtt
15.47 KB4. Building the Encoder part of the VAE.mp4
133.65 MB4. Building the Encoder part of the VAE.vtt
23.64 KB5. Building the V part of the VAE.mp4
80.34 MB5. Building the V part of the VAE.vtt
12.42 KB6. Building the Decoder part of the VAE.mp4
92.89 MB6. Building the Decoder part of the VAE.vtt
11.89 KB7. Implementing the Training operations.mp4
186.99 MB7. Implementing the Training operations.vtt
21.19 KB8. Full Code Section.html
3.96 KB9. The Keras Implementation.html
7.70 KB7. Step 6 - Recurrent Neural Network
1. Welcome to Step 6 - Recurrent Neural Network.html
0.50 KB2. Plan of Attack.mp4
10.50 MB2. Plan of Attack.vtt
3.06 KB3. What are Recurrent Neural Networks.mp4
121.09 MB3. What are Recurrent Neural Networks.vtt
21.38 KB4. The Vanishing Gradient Problem.mp4
111.17 MB4. The Vanishing Gradient Problem.vtt
18.56 KB5. LSTMs.mp4
136.52 MB5. LSTMs.vtt
25.08 KB6. LSTM Practical Intuition.mp4
187.41 MB6. LSTM Practical Intuition.vtt
18.59 KB7. LSTM Variations.mp4
20.12 MB7. LSTM Variations.vtt
4.42 KB8. Step 7 - Mixture Density Network
1. Welcome to Step 7 - Mixture Density Network.html
0.50 KB2. Introduction to the MDN-RNN.mp4
83.39 MB2. Introduction to the MDN-RNN.vtt
83.41 MB3. Mixture Density Networks.mp4
65.36 MB3. Mixture Density Networks.vtt
12.41 KB4. VAE + MDN-RNN Visualization.mp4
45.31 MB4. VAE + MDN-RNN Visualization.vtt
6.91 KB9. Step 8 - Implementing the MDN-RNN
1. Welcome to Step 8 - Implementing the MDN-RNN.html
2.81 KB10. Implementing the Training operations (Part 2).mp4
162.89 MB10. Implementing the Training operations (Part 2).vtt
17.23 KB11. Full Code Section.html
10.80 KB12. The Keras Implementation.html
5.26 KB2. Initializing all the parameters and variables of the MDN-RNN class.mp4
99.50 MB2. Initializing all the parameters and variables of the MDN-RNN class.vtt
16.44 KB3. Building the RNN - Gathering the parameters.mp4
76.58 MB3. Building the RNN - Gathering the parameters.vtt
55.30 MB4. Building the RNN - Creating an LSTM cell with Dropout.mp4
127.16 MB4. Building the RNN - Creating an LSTM cell with Dropout.vtt
19.77 KB5. Building the RNN - Setting up the Input, Target, and Output of the RNN.mp4
131.12 MB5. Building the RNN - Setting up the Input, Target, and Output of the RNN.vtt
17.92 KB6. Building the RNN - Getting the Deterministic Output of the RNN.mp4
125.49 MB6. Building the RNN - Getting the Deterministic Output of the RNN.vtt
15.04 KB7. Building the MDN - Getting the Input, Hidden Layer and Output of the MDN.mp4
146.97 MB7. Building the MDN - Getting the Input, Hidden Layer and Output of the MDN.vtt
15.02 KB8. Building the MDN - Getting the MDN parameters.mp4
109.45 MB8. Building the MDN - Getting the MDN parameters.vtt
13.21 KB9. Implementing the Training operations (Part 1).mp4
177.45 MB9. Implementing the Training operations (Part 1).vtt
18.28 KB[CourseClub.NET].url
0.12 KB[FCS Forum].url
0.13 KB[FreeCourseSite.com].url
0.12 KBtracker
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