AssemblyAI-Community/Machine-Learning-From-Scratch
Machine Learning From Scratch
Machine-Learning-From-Scratch 是一个教育性仓库，提供了使用标准 Python 编程逻辑构建的基础机器学习模型实现。它作为一个资源，帮助用户通过从零开始构建常见的统计和预测算法，而非依赖高级机器学习框架，来理解其内部机制。
该项目优先考虑算法设计的透明度，利用数学原语和向量化数组计算来揭示底层的微积分和统计逻辑。通过将学习技术结构化为模块化、独立的组件，该仓库允许用户隔离地检查迭代训练循环和基于梯度的优化过程。
该集合涵盖了广泛的数据科学技术，专注于核心处理步骤和模型训练过程的手动实现。该仓库旨在通过演示预测模型如何通过基础编程和分析实践来运作，从而支持数据科学技能的发展。
Features
- Machine Learning Implementations - Provides a collection of fundamental machine learning models built from scratch to demonstrate underlying mathematical mechanics.
- From-Scratch ML Model Implementations - Provides implementations of fundamental machine learning models built from first principles for educational study.
- Machine Learning Education - Teaches machine learning mechanics by building fundamental models from scratch using basic programming logic.
- Gradient-Based Learning - Implements gradient-based learning algorithms by manually calculating partial derivatives to update model parameters.
