Overview: Python and open-source tools make AI development accessible to everyone.Pre-trained models and AutoML speed up ...

Overview A mix of beginner and advanced-level books to suit various learning needs.Each book blends theory with practical ...

Official support for free-threaded Python, and free-threaded improvements Python’s free-threaded build promises true parallelism for threads in Python programs by removing the Global Interpreter Lock ...

In today's data-driven environment, Python has become the mainstream language in the fields of machine learning and data science due to its concise syntax, rich library support, and active community, ...

Google Colab is useful for anyone exploring Python, data science, or machine learning without a powerful computer. Students and beginners can use Colab to explore Python and data science directly in ...

Programming languages constantly change, and developers need to stay current with what's working in the real world.

Looking for the best Raspberry Pi projects of 2025? Our top 10 list shows you how to build a retro game console, a weather ...

By 2026, AI agents will run workflows — but only if we stop chasing 'super agents' and design them to stay in their lanes.

在过去几年中，人工智能（AI）与量子运算的结合已经从理论探讨转向实际研究和早期商业应用。如今，专业人士在高性能计算（HPC）、超级运算、AI及相关技术领域中，能够观察到由混合架构、量子机器学习技术和新型软件工具驱动的真实案例。

那么在本篇文章中将带着大家从零开始进行Demo的烧录（测试意图）、模型训练，转换成C 语言数组。然后到模型的部署，最终实现和模型一样的效果。阅读这篇文章你最好具备一些基础的Machine learning和Deep learning知识。