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机器学习
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- 维基百科
Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field is closely related to artificial intelligence and computational statistics.
An Open Source Machine Learning Framework for Everyone
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
X-Ray Vision for your infrastructure!
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
List of Computer Science courses with video lectures.
Tesseract Open Source OCR Engine (main repository)
Deep Learning for humans
The Patterns of Scalable, Reliable, and Performant Large-Scale Systems
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
The world's simplest facial recognition api for Python and the command line
Deepfakes Software For All
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
The Julia Programming Language
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
Investment Research for Everyone, Everywhere.