Udemy - PyTorch The Complete Guide 2022

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[ DevCourseWeb.com ] Udemy - PyTorch The Complete Guide 2022
  • Get Bonus Downloads Here.url (0.2 KB)
  • ~Get Your Files Here ! 1. Introduction
    • 1. Course structure.mp4 (9.5 MB)
    • 2. How To Make The Most Out Of This Course.mp4 (8.2 MB)
    • 3. Important note on tool.mp4 (5.1 MB)
    • 4. What is neuron.mp4 (7.2 MB)
    • 5. What is Multilayer Neural Network.mp4 (8.9 MB)
    • 6. Simple Neural Network with Pytorch Implementation Part 1.mp4 (159.0 MB)
    • 6.2 Pytorch_introduction.ipynb (7.8 KB)
    • 7. Simple Neural Network with Pytorch Implementation Part 2.mp4 (148.9 MB)
    • 7.1 Pytorch_introduction (1).ipynb (18.2 KB)
    • 8. Simple Neural Network with Pytorch Implementation Part 3.mp4 (70.3 MB)
    • 8.1 Pytorch_introduction (2).ipynb (28.8 KB)
    • pytorch_dataset
      • test.csv (363.5 KB)
      • train.csv (1.8 MB)
      2. Image Processing with Pytorch
      • 1. More Explanation about CNN.mp4 (42.0 MB)
      • 10. Project Time MNIST Implementation Part 6.mp4 (145.0 MB)
      • 10.1 Pytorch_CNN (2).ipynb (406.5 KB)
      • 2. What is Convolution Neural Network.mp4 (44.2 MB)
      • 3. what is convolution layer.mp4 (16.2 MB)
      • 4. what is pooling layer.mp4 (20.9 MB)
      • 5. Project Time MNIST Implementation Part 1 Importing libraries and data.mp4 (148.7 MB)
      • 5.1 Pytorch_CNN.ipynb (65.0 KB)
      • 6. Project Time MNIST Implementation Part 2.mp4 (72.1 MB)
      • 6.1 Copy_of_Pytorch_CNN.ipynb (250.5 KB)
      • 7. Project Time MNIST Implementation Part 3.mp4 (82.8 MB)
      • 8. Project Time MNIST Implementation Part 4.mp4 (51.4 MB)
      • 8.1 Copy_of_Pytorch_CNN (1).ipynb (209.5 KB)
      • 9. Project Time MNIST Implementation Part 5.mp4 (131.5 MB)
      • 9.1 Pytorch_CNN (1).ipynb (355.1 KB)
      3. GAN with Pytorch
      • 1. Introduction.mp4 (172.3 MB)
      • 1.1 GAN.ipynb (4.3 KB)
      • 2. GAN Project Importing libraries and datas.mp4 (68.9 MB)
      • 2.1 GAN (1).ipynb (7.1 KB)
      • 3. GAN Project Generator Construction.mp4 (99.0 MB)
      • 3.1 GAN (3).ipynb (12.7 KB)
      • 4. GAN Project Discriminator Construction.mp4 (110.9 MB)
      • 4.1 GAN (4).ipynb (17.3 KB)
      • 5. GAN Project Defining optimizer and loss.mp4 (33.3 MB)
      • 5.1 GAN (5).ipynb (18.1 KB)
      • 6. GAN Project Fully Connected Network and results.mp4 (130.3 MB)
      • 6.1 GAN (7).ipynb (28.9 KB)
      4. NLP with Pytorch
      • 1. Introduction to Recurrent Neural Network.mp4 (59.4 MB)
      • 1.1 Introduction_to_Recurrent_Neural_Network.ipynb (1.9 KB)
      • 10. Language Model Implementation Part 1 (Explanation).mp4 (89.7 MB)
      • 10.1 Language_Model (1).ipynb (7.2 KB)
      • 11. Language Model Implementation Part 2 with detailed Explanation.mp4 (73.9 MB)
      • 11.1 Language_Model (2).ipynb (9.1 KB)
      • 12. Language Model Implementation Part 3 with detailed Explanation.mp4 (66.7 MB)
      • 12.1 Language_Model (3).ipynb (11.1 KB)
      • 13. Language Model Implementation final Part.mp4 (64.4 MB)
      • 13.1 Language_Model (4).ipynb (30.2 KB)
      • 14. Language Model Implementation final Part (Explaination).mp4 (44.9 MB)
      • 14.1 Language_Model (5).ipynb (31.7 KB)
      • 2. Recurrent Neural Network Implementation Part 1.mp4 (91.3 MB)
      • 2.1 Introduction_to_Recurrent_Neural_Network (1).ipynb (60.5 KB)
      • 3. Recurrent Neural Network Part 1 Explanation.mp4 (157.8 MB)
      • 3.1 Introduction_to_Recurrent_Neural_Network (2).ipynb (8.8 KB)
      • 4. Recurrent Neural Network Implementation Part 2.mp4 (91.1 MB)
      • 5. Recurrent Neural Network Part 2 Explanation.mp4 (68.7 MB)
      • 5.1 Introduction_to_Recurrent_Neural_Network (4).ipynb (17.9 KB)
      • 6. Introduction to Long short term Memory.mp4 (63.6 MB)
      • 6.1 Introduction_to_Long_Short_term_memory_Networks.ipynb (2.5 KB)
      • 7. LSTMs Implementation Part 1.mp4 (52.6 MB)
      • 7.1 Introduction_to_Long_Short_term_memory_Networks (1).ipynb (7.3 KB)
      • 8. LSTMs Implementation Part 1 Explanation and final implementation.mp4 (88.0 MB)
      • 8.1 Introduction_to_Long_Short_term_memory_Networks (2).ipynb (10.3 KB)
      • 9. Language Model Implementation Part 1.mp4 (93.2 MB)
      • 9.1 Language_Model.ipynb (5.2 KB)
      • 9.2 warandpeace.txt (3.2 MB)
      5. Reinforcement with Pytorch
      • 1. What is Reinforcement Learning and Why we need Reinforcement Learning.mp4 (38.7 MB)
      • 10. Keras DQN.mp4 (35.4 MB)
      • 11. Cart Pole Implementation Part 1.mp4 (38.1 MB)
      • 12. Cart Pole Implementation Part 2.mp4 (96.2 MB)
      • 13. Cart Pole Implementation Part 3.mp4 (40.0 MB)
      • 14. Cart Pole Implementation Final Part.mp4 (12.8 MB)
      • 14.1 Cart_Pole.py (1.6 KB)
      • 15. Developing hill climbing part 1.mp4 (18.6 MB)
      • 16. Developing hill climbing part 2.mp4 (92.8 MB)
      • 17. Developing hill climbing part 3.mp4 (53.3 MB)
      • 18. Developing hill climbing final Part.mp4 (49.2 MB)
      • 18.1 hill_climbing.py (2.9 KB)
      • 2. Introduction to Reward.mp4 (64.8 MB)
      • 3. Introduction to the agent, environment, action and observation.mp4 (101.0 MB)
      • 4. How to set up the environment.mp4 (34.8 MB)
      • 5. Introduction to OpenAI Gym.mp4 (27.6 MB)
      • 6. Introduction to Robot Control and three laws of Robotics.mp4 (54.9 MB)
      • 7. Short robotics timeline and Automatic control.mp4 (69.9 MB)
      • 8. Reinforcement learning basics and Agent-environment interface.mp4 (72.7 MB)
      • 9. Reinforcement Learning Algorithm.mp4 (90.2 MB)
      6. Thank you
      • 1. Thank you.mp4 (23.3 MB)
      • Bonus Resources.txt (0.4 KB)

Description

PyTorch The Complete Guide 2022



https://DevCourseWeb.com

Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.81 GB | Duration: 9h 31m

Learn how to create state of the art neural networks for deep learning with Facebook's PyTorch Deep Learning library!

What you'll learn
Pandas
Pytorch
Numpy
Artificial Neural Networks (ANN)
Generative adversarial network (GAN)
Convolution Neural Network (CNN)
Recurrent Neural Network (RNN)
Google Colab .
Matplotlib.
Long Short Term Memory (LSTM)
Language Model
Reinforcement Learning
OpenAI Gym

Requirements
There will be no Prerequisites.
Basic knowledge of Python will be good.
But everything will be taught from the round up.



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Udemy - PyTorch The Complete Guide 2022


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3.8 GB
seeders:7
leechers:11
Udemy - PyTorch The Complete Guide 2022


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