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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.
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
Visualizer for neural network, deep learning and machine learning models
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
machine learning and deep learning tutorials, articles and other resources
深度学习入门教程, 优秀文章, Deep Learning Tutorial
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
深度学习入门开源书，基于TensorFlow 2.0案例实战。Open source Deep Learning book, based on TensorFlow 2.0 framework.
Low-code framework for building custom LLMs, neural networks, and other AI models
My blogs and code for machine learning. http://cnblogs.com/pinard
NSFW detection on the client-side via TensorFlow.js
Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀
ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution
Collection of Open Source Projects Related to GPT，GPT相关开源项目合集🚀、精选🔥🔥
Unified embedding generation and search engine. Also available on cloud - cloud.marqo.ai
Collection of AI-related utilities. Welcome to submit issues and pull requests /收藏AI相关的实用工具，欢迎提交issues 或者pull requests
Tools to Design or Visualize Architecture of Neural Network
Debugging, monitoring and visualization for Python Machine Learning and Data Science
A curated list of the latest breakthroughs in AI (in 2022) by release date with a clear video explanation, link to a more in-depth article, and code.