集合論:Set theory

アルゴリズム:Algorithms

Statistical Learning Theory

Theory on statistical properties of machine learning algorithms utilized in digital transformation, artificial intelligence, and machine learning tasks (law of large uniform numbers, universal kernel, discriminant fitting loss)
2022.08.13
アルゴリズム:Algorithms微分積分:Calculus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
グラフ理論

Optimization for the First Time Reading Notes

Optimization for the First Time Reading Notes From Optimization for Beginners This book is explained in d...
2022.08.06
グラフ理論ベイズ推定微分積分:Calculus最適化:Optimization機械学習:Machine Learning深層学習:Deep Learning確率・統計:Probability and Statistics線形代数:Linear Algebra集合論:Set theory
アルゴリズム:Algorithms

The Impact of Blockchain: A Disruptive Technology that is Overturning the Social Structure from Bitcoin, FinTech to IoT – Reading Notes

Mathematics  Machine Learning Technology  Artificial Intelligence Technology  Algorithm  Digital Transformation Technolo...
2022.08.05
アルゴリズム:Algorithmsグラフ理論セキュリティ微分積分:Calculus数理論理学線形代数:Linear Algebra集合論:Set theory
アルゴリズム:Algorithms

Protected: Non-parametric Bayesian and clustering(1)Dirichlet distribution and infinite mixture Gaussian model

Analysis with a mixed Gaussian model that extends the Dirichlet distribution to infinite dimensions as a nonparametric Bayesian approach in stochastic generative models used in digital transformation artificial intelligence, and machine learning
2022.06.28
アルゴリズム:Algorithmsグラフ理論ベイズ推定微分積分:Calculus推論技術:inference Technology最適化:Optimization機械学習:Machine Learning深層学習:Deep Learning確率・統計:Probability and Statistics線形代数:Linear Algebra集合論:Set theory
アルゴリズム:Algorithms

Protected: Overview of Gaussian Processes (1) Gaussian Processes and Kernel Tricks

Overview of the theory of Gaussian processes (support vector machines, related vector machines, RVMs, RBF kernels, kernel functions), which are dimensionless multivariate Gaussian distribution models with no specified parameters among stochastic generative models used in digital transformation, artificial intelligenceand machine learningtasks.
2022.06.27
アルゴリズム:Algorithmsグラフ理論ベイズ推定微分積分:Calculus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
ベイズ推定

Introduction to Probability Theory Reading Notes

Introduction to Probability Theory Reading Notes From Introduction to Probability Theory 「It is said that...
2022.06.25
ベイズ推定数理論理学最適化:Optimization確率・統計:Probability and Statistics集合論:Set theory
Symbolic Logic

Creating Logic, Part 2: Expanding Logic Reading Notes

Fundamentals of logic (predicate logic and tableau, PPL, IPL) in mathematical logic utilized for reasoning mechanisms in artificial intelligence tasks.
2021.11.16
Symbolic Logic推論技術:inference Technology数理論理学:Mathematical logic集合論:Set theory
幾何学:Geometry

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
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