ICT技術:ICT Technology

Machine Learning Professional Series – Relational Data Learning Post-Reading Notes

Overview of relational data learning to extract the meaning and knowledge behind information used in digital transformation , artificial intelligence , and machine learning tasks.

2021.12.03

地理空間情報処理推論技術:inference Technology機械学習:Machine Learning画像認識技術自然言語処理:Natural Language Processing音声信号認識技術

Protected: Applications of Markov chain Monte Carlo methods (Bayesian inference)

Overview of the application of MCMC methods to Bayesian inference for digital transformation , artificial intelligence , and machine learning tasks, and description of various algorithms

2021.12.02

C言語機械学習:Machine Learning確率・統計:Probability and Statistics自然言語処理:Natural Language Processing

Protected: MCMC method for calculating stochastic integrals: Algorithms other than Metropolis method (HMC method)

Algorithm and C implementation of the Hybrid Monte Calro method applied to complex stochastic integral calculations for digital transformation and artificial intelligence tasks.

2021.11.29

C言語深層学習:Deep Learning確率・統計:Probability and Statistics自然言語処理:Natural Language Processing

Lisp Function Programming for the First Time reading notes

A Textbook of the LISP Language as an Explanation of Functional Programming

2021.11.28

LISP推論技術:inference Technology

Protected: MCMC Method for Stochastic Integral Calculations: Multivariate Metropolis Algorithm

MCMC Method for Stochastic Integral Computation for Digital Transformation and Artificial Intelligence Tasks: The Multivariate Metropolis Algorithm

2021.11.27

C言語機械学習:Machine Learning確率・統計:Probability and Statistics自然言語処理:Natural Language Processing

Protected: A concrete algorithm for Markov chain Monte Carlo: Metropolis method (2) application and efficiency

An Overview of MCMC Efficiency Using Metropolis Method for Stochastic Integral Computation for Digital Trasformation and Artificial Intelligence Tasks

2021.11.26

C言語機械学習:Machine Learning確率・統計:Probability and Statistics自然言語処理:Natural Language Processing

Protected: A concrete algorithm for Markov chain Monte Carlo: Metropolis method (1)Overview

Overview of the Metropolis method in MCMC methods used for probability integration and other aspects of machine learning for digital transformation and artificial intelligence tasks.

2021.11.25

C言語機械学習:Machine Learning確率・統計:Probability and Statistics自然言語処理:Natural Language Processing

Protected: General Theory of MCMC Methods: Applying Markov Chains to Monte Carlo Methods

Application of Markov Chains to Monte Carlo methods for efficient computation of probability/combination and other integrals for digital transformation and artificial intelligence tasks.

2021.11.24

C言語機械学習:Machine Learning確率・統計:Probability and Statistics自然言語処理:Natural Language Processing

Chatbots: The Future Transformed by the Evolution of AI and Robotics – Reading Memo

Chatbot technology trends, business development and future prospects for use in digital transformation and artificial intelligence tasks

2021.11.23

web技術:web technologyチャットボット自然言語処理:Natural Language Processing

Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp Reading Memo

Explanation of basic ideas of various artificial intelligence techniques using LISP (GPS, ELIZA, SUDENT, symbol processing systems, natural language processing systems, Prolog, expert systems, etc.)

2021.11.23

LISPprolog推論技術:inference Technology数理論理学:Mathematical logic