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[FreeTutorials.Us] Udemy - Artificial Intelligence Masterclass
magnet:?xt=urn:btih:0cbfbe4bdd220e48976639ff1b095c571a8a26c6&dn=[FreeTutorials.Us] Udemy - Artificial Intelligence Masterclass
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文件列表详情
0cbfbe4bdd220e48976639ff1b095c571a8a26c6
infohash:
69
文件数量
6.1 GB
文件大小
2019-7-16 05:48
创建日期
2024-7-21 18:25
最后访问
相关分词
FreeTutorials
Us
Udemy
-
Artificial
Intelligence
Masterclass
1. Introduction/1. Updates on Udemy Reviews.mp4 22.03 MB
1. Introduction/2. Introduction + Course Structure + Demo.mp4 195.34 MB
1. Introduction/4. Your Three Best Resources.mp4 134.49 MB
10. Step 9 - Reinforcement Learning/2. What is Reinforcement Learning.mp4 68.6 MB
10. Step 9 - Reinforcement Learning/3. A Pseudo Implementation of Reinforcement Learning for the Full World Model.mp4 154.25 MB
11. Step 10 - Deep NeuroEvolution/2. Deep NeuroEvolution.mp4 108.84 MB
11. Step 10 - Deep NeuroEvolution/3. Evolution Strategies.mp4 119.44 MB
11. Step 10 - Deep NeuroEvolution/4. Genetic Algorithms.mp4 149.11 MB
11. Step 10 - Deep NeuroEvolution/5. Covariance-Matrix Adaptation Evolution Strategy (CMA-ES).mp4 144.06 MB
11. Step 10 - Deep NeuroEvolution/6. Parameter-Exploring Policy Gradients (PEPG).mp4 143.9 MB
11. Step 10 - Deep NeuroEvolution/7. OpenAI Evolution Strategy.mp4 108.09 MB
12. The Final Run/1. The Whole Implementation.mp4 273.65 MB
12. The Final Run/3. Installing the required packages.mp4 158.71 MB
12. The Final Run/4. The Final Race Human Intelligence vs. Artificial Intelligence.mp4 125.09 MB
12. The Final Run/5. THANK YOU bonus video.mp4 29.21 MB
2. Step 1 - Artificial Neural Network/2. Plan of Attack.mp4 15.85 MB
2. Step 1 - Artificial Neural Network/3. The Neuron.mp4 98.79 MB
2. Step 1 - Artificial Neural Network/4. The Activation Function.mp4 45.36 MB
2. Step 1 - Artificial Neural Network/5. How do Neural Networks work.mp4 81.94 MB
2. Step 1 - Artificial Neural Network/6. How do Neural Networks learn.mp4 112.11 MB
2. Step 1 - Artificial Neural Network/7. Gradient Descent.mp4 60.62 MB
2. Step 1 - Artificial Neural Network/8. Stochastic Gradient Descent.mp4 67.29 MB
2. Step 1 - Artificial Neural Network/9. Backpropagation.mp4 43.14 MB
3. Step 2 - Convolutional Neural Network/10. Softmax & Cross-Entropy.mp4 117.97 MB
3. Step 2 - Convolutional Neural Network/2. Plan of Attack.mp4 21.81 MB
3. Step 2 - Convolutional Neural Network/3. What are Convolutional Neural Networks.mp4 107.97 MB
3. Step 2 - Convolutional Neural Network/4. Step 1 - The Convolution Operation.mp4 97.93 MB
3. Step 2 - Convolutional Neural Network/5. Step 1 Bis - The ReLU Layer.mp4 53.44 MB
3. Step 2 - Convolutional Neural Network/6. Step 2 - Pooling.mp4 140.17 MB
3. Step 2 - Convolutional Neural Network/7. Step 3 - Flattening.mp4 7.94 MB
3. Step 2 - Convolutional Neural Network/8. Step 4 - Full Connection.mp4 194.26 MB
3. Step 2 - Convolutional Neural Network/9. Summary.mp4 30.33 MB
4. Step 3 - AutoEncoder/10. Stacked AutoEncoders.mp4 16.44 MB
4. Step 3 - AutoEncoder/11. Deep AutoEncoders.mp4 11.97 MB
4. Step 3 - AutoEncoder/2. Plan of Attack.mp4 15.85 MB
4. Step 3 - AutoEncoder/3. What are AutoEncoders.mp4 94.61 MB
4. Step 3 - AutoEncoder/4. A Note on Biases.mp4 8.61 MB
4. Step 3 - AutoEncoder/5. Training an AutoEncoder.mp4 50.3 MB
4. Step 3 - AutoEncoder/6. Overcomplete Hidden Layers.mp4 28.06 MB
4. Step 3 - AutoEncoder/7. Sparse AutoEncoders.mp4 57.45 MB
4. Step 3 - AutoEncoder/8. Denoising AutoEncoders.mp4 24.1 MB
4. Step 3 - AutoEncoder/9. Contractive AutoEncoders.mp4 20.55 MB
5. Step 4 - Variational AutoEncoder/2. Introduction to the VAE.mp4 72.81 MB
5. Step 4 - Variational AutoEncoder/3. Variational AutoEncoders.mp4 26.31 MB
5. Step 4 - Variational AutoEncoder/4. Reparameterization Trick.mp4 26.41 MB
6. Step 5 - Implementing the CNN-VAE/2. Introduction to Step 5.mp4 58.85 MB
6. Step 5 - Implementing the CNN-VAE/3. Initializing all the parameters and variables of the CNN-VAE class.mp4 71.72 MB
6. Step 5 - Implementing the CNN-VAE/4. Building the Encoder part of the VAE.mp4 133.64 MB
6. Step 5 - Implementing the CNN-VAE/5. Building the V part of the VAE.mp4 80.33 MB
6. Step 5 - Implementing the CNN-VAE/6. Building the Decoder part of the VAE.mp4 92.89 MB
6. Step 5 - Implementing the CNN-VAE/7. Implementing the Training operations.mp4 186.98 MB
7. Step 6 - Recurrent Neural Network/2. Plan of Attack.mp4 10.5 MB
7. Step 6 - Recurrent Neural Network/3. What are Recurrent Neural Networks.mp4 121.09 MB
7. Step 6 - Recurrent Neural Network/4. The Vanishing Gradient Problem.mp4 111.17 MB
7. Step 6 - Recurrent Neural Network/5. LSTMs.mp4 136.52 MB
7. Step 6 - Recurrent Neural Network/6. LSTM Practical Intuition.mp4 187.41 MB
7. Step 6 - Recurrent Neural Network/7. LSTM Variations.mp4 20.12 MB
8. Step 7 - Mixture Density Network/2. Introduction to the MDN-RNN.mp4 83.39 MB
8. Step 7 - Mixture Density Network/3. Mixture Density Networks.mp4 65.35 MB
8. Step 7 - Mixture Density Network/4. VAE + MDN-RNN Visualization.mp4 45.3 MB
9. Step 8 - Implementing the MDN-RNN/10. Implementing the Training operations (Part 2).mp4 162.89 MB
9. Step 8 - Implementing the MDN-RNN/2. Initializing all the parameters and variables of the MDN-RNN class.mp4 99.49 MB
9. Step 8 - Implementing the MDN-RNN/3. Building the RNN - Gathering the parameters.mp4 76.58 MB
9. Step 8 - Implementing the MDN-RNN/4. Building the RNN - Creating an LSTM cell with Dropout.mp4 127.16 MB
9. Step 8 - Implementing the MDN-RNN/5. Building the RNN - Setting up the Input, Target, and Output of the RNN.mp4 131.12 MB
9. Step 8 - Implementing the MDN-RNN/6. Building the RNN - Getting the Deterministic Output of the RNN.mp4 125.49 MB
9. Step 8 - Implementing the MDN-RNN/7. Building the MDN - Getting the Input, Hidden Layer and Output of the MDN.mp4 146.98 MB
9. Step 8 - Implementing the MDN-RNN/8. Building the MDN - Getting the MDN parameters.mp4 109.44 MB
9. Step 8 - Implementing the MDN-RNN/9. Implementing the Training operations (Part 1).mp4 177.44 MB
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