ai
Note
ai | Note | |
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6 | 48 | |
19 | 35 | |
- | - | |
3.5 | 9.9 | |
about 1 month ago | 2 days ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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ai
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Made the YouTube Series Implementing ML Models Using NumPy
GitHub (for model impls and other series): https://github.com/oniani/ai
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[D] What advanced models would you like to see implemented from scratch?
All of the videos are and will be available on my YouTube channel. Implementations are and will be in this GitHub repo.
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[N] I Have Released the YouTube Series Discussing and Implementing Activation Functions
GitHub: https://github.com/oniani/ai
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Implementing Logistic Regression from Scratch
Link to the YouTube video: https://www.youtube.com/watch?v=YDa3rX9yLCE Link to the repo containing the code: https://github.com/oniani/ai
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[N] AI/ML Model API Design, Numerical Stability, and More Models from Scratch! (stylepoint)
Repository for the AI/ML series - oniani/ai.
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Implementing Machine Learning Models From Scratch (stylepoint)
Thanks! One thing to note about that implementation is that we could have passed features and labels directly to the fit method. This would avoid unnecessary data copying (i.e., storing data inside the LinearRegression class). I have already updated the GitHub codebase.
Note
- Easily implement parallel training.
- This project allows you to easily implement parallel training with the multiprocessing module.
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Train neural networks in parallel using Python's multiprocessing module.
https://github.com/NoteDancing/Note This project allows you to train neural network in parallel using Python's multiprocessing module.
- A system for deep learning and reinforcement learning.
- A system for deep learning and reinforcement learning. (r/MachineLearning)
- [P] A system for deep learning and reinforcement learning.
What are some alternatives?
deep-RL-trading - playing idealized trading games with deep reinforcement learning
deep-significance - Enabling easy statistical significance testing for deep neural networks.
softlearning - Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official implementation of the Soft Actor-Critic algorithm.
quickai - QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
muzero-general - MuZero
cleanrl - High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
neptune-contrib - This library is a location of the LegacyLogger for PyTorch Lightning.
pytorch-A3C - Simple A3C implementation with pytorch + multiprocessing
Muzero - Pytorch Implementation of MuZero for gym environment. It support any Discrete , Box and Box2D configuration for the action space and observation space.
Andrew-NG-Notes - This is Andrew NG Coursera Handwritten Notes.
EmoPy - A deep neural net toolkit for emotion analysis via Facial Expression Recognition (FER)
drq - DrQ: Data regularized Q