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[] Udemy - PyTorch Deep Learning and Artificial Intelligence

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  • 文件大小:1GB
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文件列表

  1. 18. Setting up your Environment (FAQ by Student Request)/3. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.mp4.!qB 167MB
  2. 18. Setting up your Environment (FAQ by Student Request)/1. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4.!qB 151MB
  3. 11. Deep Reinforcement Learning (Theory)/2. Elements of a Reinforcement Learning Problem.mp4.!qB 85MB
  4. 5. Convolutional Neural Networks/5. CNN Architecture.mp4.!qB 69MB
  5. 8. Recommender Systems/4. Recommender Systems with Deep Learning Code (pt 2).mp4.!qB 69MB
  6. 3. Machine Learning and Neurons/6. Moore's Law Notebook.mp4.!qB 65MB
  7. 2. Google Colab/1. Intro to Google Colab, how to use a GPU or TPU for free.mp4.!qB 60MB
  8. 16. In-Depth Gradient Descent/5. Adam (pt 1).mp4.!qB 55MB
  9. 12. Stock Trading Project with Deep Reinforcement Learning/2. Data and Environment.mp4.!qB 53MB
  10. 11. Deep Reinforcement Learning (Theory)/13. Deep Q-Learning DQN (pt 2).mp4.!qB 52MB
  11. 7. Natural Language Processing (NLP)/9. VIP Making Predictions with a Trained NLP Model.mp4.!qB 49MB
  12. 13. VIP Uncertainty Estimation/1. Custom Loss and Estimating Prediction Uncertainty.mp4.!qB 44MB
  13. 3. Machine Learning and Neurons/16. Train Sets vs. Validation Sets vs. Test Sets.mp4.!qB 42MB
  14. 5. Convolutional Neural Networks/9. CNN for Fashion MNIST.mp4.!qB 41MB
  15. 6. Recurrent Neural Networks, Time Series, and Sequence Data/1. Sequence Data.mp4.!qB 38MB
  16. 1. Introduction/1. Welcome.mp4.!qB 36MB
  17. 6. Recurrent Neural Networks, Time Series, and Sequence Data/7. RNN for Time Series Prediction.mp4.!qB 33MB
  18. 6. Recurrent Neural Networks, Time Series, and Sequence Data/15. Stock Return Predictions using LSTMs (pt 2).mp4.!qB 32MB
  19. 7. Natural Language Processing (NLP)/6. Text Classification with LSTMs.mp4.!qB 31MB
  20. 20. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4.!qB 29MB
  21. 5. Convolutional Neural Networks/6. CNN Code Preparation (part 1).mp4.!qB 28MB
  22. 5. Convolutional Neural Networks/13. Improving CIFAR-10 Results.mp4.!qB 21MB
  23. 6. Recurrent Neural Networks, Time Series, and Sequence Data/10. GRU and LSTM (pt 2).mp4.!qB 20MB
  24. 8. Recommender Systems/2. Recommender Systems with Deep Learning Code Preparation.mp4.!qB 19MB
  25. 12. Stock Trading Project with Deep Reinforcement Learning/7. Code pt 3.mp4.!qB 18MB
  26. 11. Deep Reinforcement Learning (Theory)/11. Q-Learning.mp4.!qB 16MB
  27. 6. Recurrent Neural Networks, Time Series, and Sequence Data/17. Other Ways to Forecast.mp4.!qB 14MB
  28. 11. Deep Reinforcement Learning (Theory)/5. The Return.mp4.!qB 13MB
  29. 18. Setting up your Environment (FAQ by Student Request)/2. Windows-Focused Environment Setup 2018.mp4.!qB 6MB
  30. 13. VIP Uncertainty Estimation/2. Estimating Prediction Uncertainty Code.mp4.!qB 6MB
  31. 11. Deep Reinforcement Learning (Theory)/14. How to Learn Reinforcement Learning.mp4.!qB 5MB
  32. 1. Introduction/2. Overview and Outline.mp4.!qB 4MB
  33. 8. Recommender Systems/1. Recommender Systems with Deep Learning Theory.mp4.!qB 4MB
  34. 19. Extra Help With Python Coding for Beginners (FAQ by Student Request)/1. How to Code Yourself (part 1).mp4.!qB 2MB
  35. 16. In-Depth Gradient Descent/6. Adam (pt 2).mp4.!qB 2MB
  36. 18. Setting up your Environment (FAQ by Student Request)/3. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.vtt 28KB
  37. 16. In-Depth Gradient Descent/5. Adam (pt 1).vtt 15KB
  38. 18. Setting up your Environment (FAQ by Student Request)/1. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt 13KB
  39. 11. Deep Reinforcement Learning (Theory)/13. Deep Q-Learning DQN (pt 2).vtt 12KB
  40. 13. VIP Uncertainty Estimation/1. Custom Loss and Estimating Prediction Uncertainty.vtt 11KB
  41. 7. Natural Language Processing (NLP)/9. VIP Making Predictions with a Trained NLP Model.vtt 8KB
  42. 1. Introduction/1. Welcome.vtt 5KB
  43. 7. Natural Language Processing (NLP)/[Tutorialsplanet.NET].url 128B
  44. 20. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 0B
  45. 20. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt 0B