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Overview of Set Theory and Reference Books

What are sets for digital transformation, artificial intelligence, and machine learning task utilization for first-time learners Cantor's set theory, intuitionistic logic, quantum logic, topological spaces, Grothendieck, Goeter, Cohen, unreachable numbers, measurable numbers, axiom of determination, Frenkel's substitution axiom, von Neumann's regularity axiom, axiomatic set theory, BG set theory, Zermelo set theory, Cantor's diagonal theory reading notes

2022.09.18

数理論理学:Mathematical logic集合論:Set theory

REST API for Microservices Overview

REST API and RESTful services, key elemental technologies of microservices used for digital transformation and artificial intelligence tasks

2022.09.17

web技術:web technologyコンピューター非同期/並行処理:Asynchronous/parallel processing

Protected: Overview and history of the banded problem and its relationship to reinforcement learning/online learning

Overview and history of bandit problems utilized in digital transformation, artificial intelligence, and machine learning tasks and their relationship to reinforcement learning online learning

2022.09.16

アルゴリズム:Algorithmsバンディッド問題強化学習機械学習:Machine Learning深層学習:Deep Learning

Protected: Application of Variational Bayesian Algorithm to Mixed Gaussian Distribution Models

Application of variational Bayesian algorithms to mixed Gaussian distribution models for the computation of stochastic generative models utilized in digital transformation, artificial intelligence, and machine learning tasks (Dirichlet distribution, isotropic Gaussian distribution, free energy calculation)

2022.09.15

アルゴリズム:Algorithms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

Protected: Specific examples of graphical models

Computation of specific graphical models such as Boltzmann Machines, Mean Field Approximation, Bethe Approximation, Hidden Markov Models, Bayesian Hidden Markov Models, etc. as probabilistic generative models utilized in digital transformation, artificial intelligence and machine learning tasks.

2022.09.14

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確率・統計:Probability and Statistics線形代数:Linear Algebra

Protected: Nonparametric Bayesian Applications to Factor Analysis and Sparse Modeling

Nonparametric Bayesian models, one of the applications of probabilistic generative models utilized in digital transformation, artificial intelligence, and machine learning tasks, for factor analysis and sparse modeling (infinite latent feature model, beta-Bernoulli distribution model, Indian cuisine buffet process, binary matrix generation process)

2022.09.13

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確率・統計:Probability and Statistics線形代数:Linear Algebra集合論:Set theory

Protected: Stochastic Generative Models and Gaussian Processes(3) Representation of Probability Distributions

Stochastic generative models utilized in digital transformation, artificial intelligence, and machine learning tasks and representation of probability distributions in samples as a basis for Gaussian processes ,weighted sampling, kernel density estimation, distribution estimation using neural nets

2022.09.12

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確率・統計:Probability and Statistics線形代数:Linear Algebra

On the Road -Geibi no Michi

Ryotaro Shiba's Road to Geibi (Aki, Bingo, Hiroshima, Jodo Shinshu, Mori Motonaga, Amago Tsunehisa, Ouchi, Yoshida Town, Miyoshi, Kofun, Izumo, Hiroshima Prefecture)

2022.09.11

旅歴史紀行読書

The Power of Pure Land Buddhism and Amitabha Buddha, which introduced the concept of parallel worlds

Pure Land Buddhism (Honen, Jodo-shu, Shinran, Jodo Shinshu), which introduced the concept of a parallel world (Buddhist land) to existing Mahayana Buddhism (Hannya Sutra, Lotus Sutra) and the power of Amida Buddha (Muryotsu Sutra, Kanmyoju Sutra, Amida Sutra)

2022.09.10

仏教:Buddhism哲学:philosophy

Implementation of a Bayesian optimization tool using Clojure

Introduction of Clojure implementation of Bayesian optimization tool, a (hyperparameter) optimization tool used for digital transformation (DX), artificial intelligence (AI), and machine learning (ML) tasks, and opimx, an optimization comparison tool in R.

2022.09.09

Clojureアルゴリズム:Algorithmsガウス過程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