Machine Learning in Practice - Introduction

    Before introducing the specific algorithm, from the understanding of the framework structure of machine learning methods, the following excerpts are quoted from "Statistical Learning Methods" - Li Hang.

1. Statistical learning = statistical machine learning statistical machine learning

1.1. Features

• Tools: Computers and Networks
• Research object: data-driven
• Purpose: Predict and analyze data with a method as the center
• Theory: Probability Theory, Statistics, Information Theory, Computational Mathematics, Operations Research, Computer
• Classification: supervised learning supervised learning, unsupervised learning unsupervised learning, semi-supervised learning semi-supervised learning

1.2. Three elements of supervised learning methods: model, strategy, algorithm

For ease of understanding, these three elements can be understood from the general steps of machine learning: