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[ DevCourseWeb com ] Udemy - PyTorch The Complete Guide 2022
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1. Introduction
1. Course structure.mp4
2. How To Make The Most Out Of This Course.mp4
3. Important note on tool.mp4
4. What is neuron.mp4
5. What is Multilayer Neural Network.mp4
6. Simple Neural Network with Pytorch Implementation Part 1.mp4
6.2 Pytorch_introduction.ipynb
7. Simple Neural Network with Pytorch Implementation Part 2.mp4
7.1 Pytorch_introduction (1).ipynb
8. Simple Neural Network with Pytorch Implementation Part 3.mp4
8.1 Pytorch_introduction (2).ipynb
pytorch_dataset
test.csv
train.csv
2. Image Processing with Pytorch
1. More Explanation about CNN.mp4
10. Project Time MNIST Implementation Part 6.mp4
10.1 Pytorch_CNN (2).ipynb
2. What is Convolution Neural Network.mp4
3. what is convolution layer.mp4
4. what is pooling layer.mp4
5. Project Time MNIST Implementation Part 1 Importing libraries and data.mp4
5.1 Pytorch_CNN.ipynb
6. Project Time MNIST Implementation Part 2.mp4
6.1 Copy_of_Pytorch_CNN.ipynb
7. Project Time MNIST Implementation Part 3.mp4
8. Project Time MNIST Implementation Part 4.mp4
8.1 Copy_of_Pytorch_CNN (1).ipynb
9. Project Time MNIST Implementation Part 5.mp4
9.1 Pytorch_CNN (1).ipynb
3. GAN with Pytorch
1. Introduction.mp4
1.1 GAN.ipynb
2. GAN Project Importing libraries and datas.mp4
2.1 GAN (1).ipynb
3. GAN Project Generator Construction.mp4
3.1 GAN (3).ipynb
4. GAN Project Discriminator Construction.mp4
4.1 GAN (4).ipynb
5. GAN Project Defining optimizer and loss.mp4
5.1 GAN (5).ipynb
6. GAN Project Fully Connected Network and results.mp4
6.1 GAN (7).ipynb
4. NLP with Pytorch
1. Introduction to Recurrent Neural Network.mp4
1.1 Introduction_to_Recurrent_Neural_Network.ipynb
10. Language Model Implementation Part 1 (Explanation).mp4
10.1 Language_Model (1).ipynb
11. Language Model Implementation Part 2 with detailed Explanation.mp4
11.1 Language_Model (2).ipynb
12. Language Model Implementation Part 3 with detailed Explanation.mp4
12.1 Language_Model (3).ipynb
13. Language Model Implementation final Part.mp4
13.1 Language_Model (4).ipynb
14. Language Model Implementation final Part (Explaination).mp4
14.1 Language_Model (5).ipynb
2. Recurrent Neural Network Implementation Part 1.mp4
2.1 Introduction_to_Recurrent_Neural_Network (1).ipynb
3. Recurrent Neural Network Part 1 Explanation.mp4
3.1 Introduction_to_Recurrent_Neural_Network (2).ipynb
4. Recurrent Neural Network Implementation Part 2.mp4
5. Recurrent Neural Network Part 2 Explanation.mp4
5.1 Introduction_to_Recurrent_Neural_Network (4).ipynb
6. Introduction to Long short term Memory.mp4
6.1 Introduction_to_Long_Short_term_memory_Networks.ipynb
7. LSTMs Implementation Part 1.mp4
7.1 Introduction_to_Long_Short_term_memory_Networks (1).ipynb
8. LSTMs Implementation Part 1 Explanation and final implementation.mp4
8.1 Introduction_to_Long_Short_term_memory_Networks (2).ipynb
9. Language Model Implementation Part 1.mp4
9.1 Language_Model.ipynb
9.2 warandpeace.txt
5. Reinforcement with Pytorch
1. What is Reinforcement Learning and Why we need Reinforcement Learning.mp4
10. Keras DQN.mp4
11. Cart Pole Implementation Part 1.mp4
12. Cart Pole Implementation Part 2.mp4
13. Cart Pole Implementation Part 3.mp4
14. Cart Pole Implementation Final Part.mp4
14.1 Cart_Pole.py
15. Developing hill climbing part 1.mp4
16. Developing hill climbing part 2.mp4
17. Developing hill climbing part 3.mp4
18. Developing hill climbing final Part.mp4
18.1 hill_climbing.py
2. Introduction to Reward.mp4
3. Introduction to the agent, environment, action and observation.mp4
4. How to set up the environment.mp4
5. Introduction to OpenAI Gym.mp4
6. Introduction to Robot Control and three laws of Robotics.mp4
7. Short robotics timeline and Automatic control.mp4
8. Reinforcement learning basics and Agent-environment interface.mp4
9. Reinforcement Learning Algorithm.mp4
6. Thank you
1. Thank you.mp4
Bonus Resources.txt
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