| 1. Introduction + Course Structure + Demo.mp4 | 156.8 MB | ||
| 1. Introduction + Course Structure + Demo.vtt | 19.2 KB | ||
| 1. Welcome to Step 1 - Artificial Neural Network.html | 614.4 B | ||
| 1. Welcome to Step 10 - Deep NeuroEvolution.html | 1.1 KB | ||
| 1. Welcome to Step 2 - Convolutional Neural Network.html | 409.6 B | ||
| 1. Welcome to Step 3 - AutoEncoder.html | 409.6 B | ||
| 1. Welcome to Step 4 - Variational AutoEncoder.html | 409.6 B | ||
| 1. Welcome to Step 5 - Implementing the CNN-VAE.html | 2.3 KB | ||
| 1. Welcome to Step 6 - Recurrent Neural Network.html | 512 B | ||
| 1. Welcome to Step 7 - Mixture Density Network.html | 512 B | ||
| 1. Welcome to Step 8 - Implementing the MDN-RNN.html | 2.8 KB | ||
| 1. Welcome to Step 9 - Reinforcement Learning.html | 409.6 B | ||
| 10. Implementing the Training operations (Part 2).mp4 | 162.9 MB | ||
| 10. Implementing the Training operations (Part 2).vtt | 16.4 KB | ||
| 10. Softmax & Cross-Entropy.mp4 | 118 MB | ||
| 10. Softmax & Cross-Entropy.vtt | 22.1 KB | ||
| 10. Stacked AutoEncoders.mp4 | 16.4 MB | ||
| 10. Stacked AutoEncoders.vtt | 2.1 KB | ||
| 11. Deep AutoEncoders.mp4 | 12 MB | ||
| 11. Deep AutoEncoders.vtt | 2.4 KB | ||
| 11. Full Code Section.html | 10.8 KB | ||
| 2. Initializing all the parameters and variables of the MDN-RNN class.mp4 | 99.5 MB | ||
| 2. Initializing all the parameters and variables of the MDN-RNN class.vtt | 15.8 KB | ||
| 2. Introduction to Step 5.mp4 | 58.9 MB | ||
| 2. Introduction to Step 5.vtt | 9.4 KB | ||
| 2. Introduction to the VAE.mp4 | 103.7 MB | ||
| 2. Introduction to the VAE.vtt | 9.7 KB | ||
| 2. Plan of Attack.mp4 | 10.5 MB | ||
| 2. Plan of Attack.vtt | 3.1 KB | ||
| 2. What is Reinforcement Learning.mp4 | 68.6 MB | ||
| 2. What is Reinforcement Learning.vtt | 16 KB | ||
| 2. Your Three Best Resources.mp4 | 143.3 MB | ||
| 2. Your Three Best Resources.vtt | 11.8 KB | ||
| 3. A Pseudo Implementation of Reinforcement Learning for the Full World Model.mp4 | 154.3 MB | ||
| 3. A Pseudo Implementation of Reinforcement Learning for the Full World Model.vtt | 23.5 KB | ||
| 3. Building the RNN - Gathering the parameters.mp4 | 76.6 MB | ||
| 3. Building the RNN - Gathering the parameters.vtt | 11.3 KB | ||
| 3. Download the Resources here.html | 3 KB | ||
| 3. Initializing all the parameters and variables of the CNN-VAE class.mp4 | 71.7 MB | ||
| 3. Initializing all the parameters and variables of the CNN-VAE class.vtt | 14.9 KB | ||
| 3. The Neuron.mp4 | 98.8 MB | ||
| 3. The Neuron.vtt | 21.6 KB | ||
| 3. Variational AutoEncoders.mp4 | 26.3 MB | ||
| 3. Variational AutoEncoders.vtt | 5.4 KB | ||
| 3. What are AutoEncoders.mp4 | 94.6 MB | ||
| 3. What are AutoEncoders.vtt | 14.3 KB | ||
| 3. What are Convolutional Neural Networks.mp4 | 108 MB | ||
| 3. What are Convolutional Neural Networks.vtt | 19.4 KB | ||
| 3. What are Recurrent Neural Networks.mp4 | 121.1 MB | ||
| 3. What are Recurrent Neural Networks.vtt | 20.8 KB | ||
| 4. A Note on Biases.mp4 | 8.6 MB | ||
| 4. A Note on Biases.vtt | 1.8 KB | ||
| 4. Building the Encoder part of the VAE.mp4 | 133.7 MB | ||
| 4. Building the Encoder part of the VAE.vtt | 22.8 KB | ||
| 4. Building the RNN - Creating an LSTM cell with Dropout.mp4 | 127.2 MB | ||
| 4. Building the RNN - Creating an LSTM cell with Dropout.vtt | 19.2 KB | ||
| 4. Full Code Section.html | 409.6 B | ||
| 4. Meet your instructors!.html | 716.8 B | ||
| 4. Reparameterization Trick.mp4 | 26.4 MB | ||
| 4. Reparameterization Trick.vtt | 5.8 KB | ||
| 4. Step 1 - The Convolution Operation.mp4 | 97.9 MB | ||
| 4. Step 1 - The Convolution Operation.vtt | 20.4 KB | ||
| 4. The Activation Function.mp4 | 45.4 MB | ||
| 4. The Activation Function.vtt | 10.4 KB | ||
| 4. The Vanishing Gradient Problem.mp4 | 111.2 MB | ||
| 4. The Vanishing Gradient Problem.vtt | 18.3 KB | ||
| 5. Building the RNN - Setting up the Input, Target, and Output of the RNN.mp4 | 131.1 MB | ||
| 5. Building the RNN - Setting up the Input, Target, and Output of the RNN.vtt | 17.7 KB | ||
| 5. Building the V part of the VAE.mp4 | 80.3 MB | ||
| 5. Building the V part of the VAE.vtt | 11.8 KB | ||
| 5. How do Neural Networks work.mp4 | 81.9 MB | ||
| 5. How do Neural Networks work.vtt | 16.8 KB | ||
| 5. LSTMs.mp4 | 136.5 MB | ||
| 5. LSTMs.vtt | 24.6 KB | ||
| 5. Step 1 Bis - The ReLU Layer.mp4 | 53.4 MB | ||
| 5. Step 1 Bis - The ReLU Layer.vtt | 8.2 KB | ||
| 5. Training an AutoEncoder.mp4 | 50.3 MB | ||
| 5. Training an AutoEncoder.vtt | 8.4 KB | ||
| 6. Building the Decoder part of the VAE.mp4 | 92.9 MB | ||
| 6. Building the Decoder part of the VAE.vtt | 11.4 KB | ||
| 6. Building the RNN - Getting the Deterministic Output of the RNN.mp4 | 125.5 MB | ||
| 6. Building the RNN - Getting the Deterministic Output of the RNN.vtt | 14.4 KB | ||
| 6. How do Neural Networks learn.mp4 | 112.1 MB | ||
| 6. How do Neural Networks learn.vtt | 16.5 KB | ||
| 6. LSTM Practical Intuition.mp4 | 187.4 MB | ||
| 6. LSTM Practical Intuition.vtt | 18.4 KB | ||
| 6. Overcomplete Hidden Layers.mp4 | 28.1 MB | ||
| 6. Overcomplete Hidden Layers.vtt | 5 KB | ||
| 6. Step 2 - Pooling.mp4 | 140.2 MB | ||
| 6. Step 2 - Pooling.vtt | 18.4 KB | ||
| 7. Building the MDN - Getting the Input, Hidden Layer and Output of the MDN.mp4 | 147 MB | ||
| 7. Building the MDN - Getting the Input, Hidden Layer and Output of the MDN.vtt | 14.7 KB | ||
| 7. Gradient Descent.mp4 | 60.6 MB | ||
| 7. Gradient Descent.vtt | 12.3 KB | ||
| 7. Implementing the Training operations.mp4 | 187 MB | ||
| 7. Implementing the Training operations.vtt | 20.4 KB | ||
| 7. LSTM Variations.mp4 | 20.1 MB | ||
| 7. LSTM Variations.vtt | 4.3 KB | ||
| 7. Sparse AutoEncoders.mp4 | 57.5 MB | ||
| 7. Sparse AutoEncoders.vtt | 7.8 KB | ||
| 7. Step 3 - Flattening.mp4 | 7.9 MB | ||
| 7. Step 3 - Flattening.vtt | 2.3 KB | ||
| 8. Building the MDN - Getting the MDN parameters.mp4 | 109.5 MB | ||
| 8. Building the MDN - Getting the MDN parameters.vtt | 12.8 KB | ||
| 8. Denoising AutoEncoders.mp4 | 24.1 MB | ||
| 8. Denoising AutoEncoders.vtt | 3.2 KB | ||
| 8. Full Code Section.html | 4 KB | ||
| 8. Step 4 - Full Connection.mp4 | 194.3 MB | ||
| 8. Step 4 - Full Connection.vtt | 25 KB | ||
| 8. Stochastic Gradient Descent.mp4 | 67.3 MB | ||
| 8. Stochastic Gradient Descent.vtt | 10.8 KB | ||
| 9. Backpropagation.mp4 | 43.1 MB | ||
| 9. Backpropagation.vtt | 6.4 KB | ||
| 9. Contractive AutoEncoders.mp4 | 20.6 MB | ||
| 9. Contractive AutoEncoders.vtt | 3.1 KB | ||
| 9. Implementing the Training operations (Part 1).mp4 | 177.5 MB | ||
| 9. Implementing the Training operations (Part 1).vtt | 17.8 KB | ||
| 9. Summary.mp4 | 30.3 MB | ||
| 9. Summary.vtt | 5.4 KB | ||
| [DesireCourse.Com].txt | 716.8 B | ||
| [DesireCourse.Com].url | 0 B | ||
| ▲ 127 total files | |||
Artificial Intelligence Masterclass
Enter the new era of Hybrid AI Models optimized by Deep NeuroEvolution, with a complete toolkit of ML, DL & AI models
For More Courses Visit: https://desirecourse.com
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Udemy - IMRaD-Q1 Paper Writing and Publishing with ChatGPT and AI '26 Posted by
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