Overview of the gradient method and examples of algorithms and implementations
Gradient Descent
The gradient method is one of the widely used methods in machine learning and optimization algo...
線形代数:Linear Algebra
Overview and implementation of image recognition systems
Image Recognition System Overview
An image recognition system will be a technology in which a computer analy...
Overview and Implementation of Markov Chain Monte Carlo Methods
Overview of Markov Chain Monte Carlo Methods
Markov Chain Monte Carlo (MCMC) is a st...
Overview of Variational Bayesian Learning and Various Implementations
About Variational Methods in Machine Learning
Variational methods (Variational Methods) are used to find the op...
Why Reinforcement Learning? Application Examples, Technical Issues and Solution Approaches
Introduction
Reinforcement learning is another aspect of OpenAI, which is famous for chatGPT. the heart of ...
Overview of Bayesian Structural Time Series Models and Examples of Application and Implementation
Bayesian Structural Time Series Models
Bayesian Structural Time Series Model (BSTS) is a type of statisti...
Overview and implementation of stochastic optimization in machine learning
Overview of Stochastic Optimization in Machine Learning
Stochastic optimization represents a method of solvin...
Overview of statistical learning theory (explanation without mathematical formulas)
On the theory of statistical properties of machine learning algorithms
The theory of the statistical properties...
Overview of generalized linear models and their implementation in various languages
Generalized Linear Model Overview
The Generalized Linear Model (GLM) is a statistical modeling and machin...
Overview of Multitask Learning and Examples of Applications and Implementations
Overview of Multitasking Learning
Multi-Task Learning (Multi-Task Learning) is a machine learning techn...