線形代数:Linear Algebra

Introduction to Optimization Problems Combining Cone Optimization, Integer Optimization, and Network Models Problem Solving with Python Series

Overview of optimization techniques in machine learning using python for digital transformation (DX) and artificial intelligence (AI) tasks.

2021.10.24

python微分積分:Calculus推論技術:inference Technology機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

Protected: Matrix Decomposition -Extraction of relational features between two objects

Extraction of relationships by machine learning, matrix factorization approach, non-negative matrix factorization

2021.05.30

機械学習:Machine Learning線形代数:Linear Algebra

Protected: Clustering of symmetric relational data – Spectral clustering

Extraction of relationships, knowledge extraction and prediction, spectral clustering by machine learning for graph analysis, etc.

2021.05.28

最適化:Optimization検索技術:Search Technology機械学習:Machine Learning線形代数:Linear Algebra

Protected: Support Vector Machines – Overview

Overview of SVMs (Support Vector Machines), the basis for various machine learning methods such as classification, regression, and unsupervised learning.

2021.05.05

アルゴリズム:Algorithms最適化:Optimization機械学習:Machine Learning線形代数:Linear Algebra

Fundamentals of Computer Mathematics

Overview of computer mathematics as a basis for artificial intelligence and machine learning techniques, functions, sets, probability, simultaneous equations, differentiation, and integration.

2021.03.17

幾何学:Geometry微分積分:Calculus数理論理学:Mathematical logic最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra集合論:Set theory