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[FreeTutorials.Us] Udemy - Artificial Intelligence Masterclass
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2019-7-16 05:48
2024-12-22 10:50
152
6.1 GB
69
磁力链接
magnet:?xt=urn:btih:0cbfbe4bdd220e48976639ff1b095c571a8a26c6
迅雷链接
thunder://QUFtYWduZXQ6P3h0PXVybjpidGloOjBjYmZiZTRiZGQyMjBlNDg5NzY2MzlmZjFiMDk1YzU3MWE4YTI2YzZaWg==
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相关链接
FreeTutorials
Us
Udemy
-
Artificial
Intelligence
Masterclass
文件列表
1. Introduction/1. Updates on Udemy Reviews.mp4
22.03MB
1. Introduction/2. Introduction + Course Structure + Demo.mp4
195.34MB
1. Introduction/4. Your Three Best Resources.mp4
134.49MB
10. Step 9 - Reinforcement Learning/2. What is Reinforcement Learning.mp4
68.6MB
10. Step 9 - Reinforcement Learning/3. A Pseudo Implementation of Reinforcement Learning for the Full World Model.mp4
154.25MB
11. Step 10 - Deep NeuroEvolution/2. Deep NeuroEvolution.mp4
108.84MB
11. Step 10 - Deep NeuroEvolution/3. Evolution Strategies.mp4
119.44MB
11. Step 10 - Deep NeuroEvolution/4. Genetic Algorithms.mp4
149.11MB
11. Step 10 - Deep NeuroEvolution/5. Covariance-Matrix Adaptation Evolution Strategy (CMA-ES).mp4
144.06MB
11. Step 10 - Deep NeuroEvolution/6. Parameter-Exploring Policy Gradients (PEPG).mp4
143.9MB
11. Step 10 - Deep NeuroEvolution/7. OpenAI Evolution Strategy.mp4
108.09MB
12. The Final Run/1. The Whole Implementation.mp4
273.65MB
12. The Final Run/3. Installing the required packages.mp4
158.71MB
12. The Final Run/4. The Final Race Human Intelligence vs. Artificial Intelligence.mp4
125.09MB
12. The Final Run/5. THANK YOU bonus video.mp4
29.21MB
2. Step 1 - Artificial Neural Network/2. Plan of Attack.mp4
15.85MB
2. Step 1 - Artificial Neural Network/3. The Neuron.mp4
98.79MB
2. Step 1 - Artificial Neural Network/4. The Activation Function.mp4
45.36MB
2. Step 1 - Artificial Neural Network/5. How do Neural Networks work.mp4
81.94MB
2. Step 1 - Artificial Neural Network/6. How do Neural Networks learn.mp4
112.11MB
2. Step 1 - Artificial Neural Network/7. Gradient Descent.mp4
60.62MB
2. Step 1 - Artificial Neural Network/8. Stochastic Gradient Descent.mp4
67.29MB
2. Step 1 - Artificial Neural Network/9. Backpropagation.mp4
43.14MB
3. Step 2 - Convolutional Neural Network/10. Softmax & Cross-Entropy.mp4
117.97MB
3. Step 2 - Convolutional Neural Network/2. Plan of Attack.mp4
21.81MB
3. Step 2 - Convolutional Neural Network/3. What are Convolutional Neural Networks.mp4
107.97MB
3. Step 2 - Convolutional Neural Network/4. Step 1 - The Convolution Operation.mp4
97.93MB
3. Step 2 - Convolutional Neural Network/5. Step 1 Bis - The ReLU Layer.mp4
53.44MB
3. Step 2 - Convolutional Neural Network/6. Step 2 - Pooling.mp4
140.17MB
3. Step 2 - Convolutional Neural Network/7. Step 3 - Flattening.mp4
7.94MB
3. Step 2 - Convolutional Neural Network/8. Step 4 - Full Connection.mp4
194.26MB
3. Step 2 - Convolutional Neural Network/9. Summary.mp4
30.33MB
4. Step 3 - AutoEncoder/10. Stacked AutoEncoders.mp4
16.44MB
4. Step 3 - AutoEncoder/11. Deep AutoEncoders.mp4
11.97MB
4. Step 3 - AutoEncoder/2. Plan of Attack.mp4
15.85MB
4. Step 3 - AutoEncoder/3. What are AutoEncoders.mp4
94.61MB
4. Step 3 - AutoEncoder/4. A Note on Biases.mp4
8.61MB
4. Step 3 - AutoEncoder/5. Training an AutoEncoder.mp4
50.3MB
4. Step 3 - AutoEncoder/6. Overcomplete Hidden Layers.mp4
28.06MB
4. Step 3 - AutoEncoder/7. Sparse AutoEncoders.mp4
57.45MB
4. Step 3 - AutoEncoder/8. Denoising AutoEncoders.mp4
24.1MB
4. Step 3 - AutoEncoder/9. Contractive AutoEncoders.mp4
20.55MB
5. Step 4 - Variational AutoEncoder/2. Introduction to the VAE.mp4
72.81MB
5. Step 4 - Variational AutoEncoder/3. Variational AutoEncoders.mp4
26.31MB
5. Step 4 - Variational AutoEncoder/4. Reparameterization Trick.mp4
26.41MB
6. Step 5 - Implementing the CNN-VAE/2. Introduction to Step 5.mp4
58.85MB
6. Step 5 - Implementing the CNN-VAE/3. Initializing all the parameters and variables of the CNN-VAE class.mp4
71.72MB
6. Step 5 - Implementing the CNN-VAE/4. Building the Encoder part of the VAE.mp4
133.64MB
6. Step 5 - Implementing the CNN-VAE/5. Building the V part of the VAE.mp4
80.33MB
6. Step 5 - Implementing the CNN-VAE/6. Building the Decoder part of the VAE.mp4
92.89MB
6. Step 5 - Implementing the CNN-VAE/7. Implementing the Training operations.mp4
186.98MB
7. Step 6 - Recurrent Neural Network/2. Plan of Attack.mp4
10.5MB
7. Step 6 - Recurrent Neural Network/3. What are Recurrent Neural Networks.mp4
121.09MB
7. Step 6 - Recurrent Neural Network/4. The Vanishing Gradient Problem.mp4
111.17MB
7. Step 6 - Recurrent Neural Network/5. LSTMs.mp4
136.52MB
7. Step 6 - Recurrent Neural Network/6. LSTM Practical Intuition.mp4
187.41MB
7. Step 6 - Recurrent Neural Network/7. LSTM Variations.mp4
20.12MB
8. Step 7 - Mixture Density Network/2. Introduction to the MDN-RNN.mp4
83.39MB
8. Step 7 - Mixture Density Network/3. Mixture Density Networks.mp4
65.35MB
8. Step 7 - Mixture Density Network/4. VAE + MDN-RNN Visualization.mp4
45.3MB
9. Step 8 - Implementing the MDN-RNN/10. Implementing the Training operations (Part 2).mp4
162.89MB
9. Step 8 - Implementing the MDN-RNN/2. Initializing all the parameters and variables of the MDN-RNN class.mp4
99.49MB
9. Step 8 - Implementing the MDN-RNN/3. Building the RNN - Gathering the parameters.mp4
76.58MB
9. Step 8 - Implementing the MDN-RNN/4. Building the RNN - Creating an LSTM cell with Dropout.mp4
127.16MB
9. Step 8 - Implementing the MDN-RNN/5. Building the RNN - Setting up the Input, Target, and Output of the RNN.mp4
131.12MB
9. Step 8 - Implementing the MDN-RNN/6. Building the RNN - Getting the Deterministic Output of the RNN.mp4
125.49MB
9. Step 8 - Implementing the MDN-RNN/7. Building the MDN - Getting the Input, Hidden Layer and Output of the MDN.mp4
146.98MB
9. Step 8 - Implementing the MDN-RNN/8. Building the MDN - Getting the MDN parameters.mp4
109.44MB
9. Step 8 - Implementing the MDN-RNN/9. Implementing the Training operations (Part 1).mp4
177.44MB
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