Machine Learning 技术汇总

【Convolutional neural network，卷积神经网络】https://blog.csdn.net/jiaoyangwm/article/details/80011656

【粒子群优化算法】：  https://blog.csdn.net/daaikuaichuan/article/details/81382794

【常用的分类算法】： https://blog.csdn.net/smillest/article/details/52682771

【最小二乘法】： https://blog.csdn.net/jairuschan/article/details/7517773

【FCM (Fuzzy C-Means) 模糊C聚类】  https://blog.csdn.net/zjsghww/article/details/50922168

【高斯曲线拟合原理及实现 】 https://blog.csdn.net/c914620529/article/details/50393238

注意理解 -- 高斯混合模型

【支持向量机】 

• https://baike.baidu.com/item/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA/9683835?fr=aladdin
• https://blog.csdn.net/b285795298/article/details/81977271
• https://blog.csdn.net/qq_35992440/article/details/80987664

【Singular Value Decomposition】

IN WIKI (https://en.wikipedia.org/wiki/Singular_value_decomposition)

In linear algebra, the singular value decomposition (SVD) is a factorization of a real or complex matrix. It is the generalization of the eigendecomposition of a positive semidefinite normal matrix (for example, a symmetric matrix with positive eigenvalues) to any {\displaystyle m\times n}