artificial intelligence

最適化:Optimization

Protected: Anomaly detection by T2 method for hoteling-Mahalanobis distance and chi-square distribution

Anomaly and change detection using the T2 method (Mahalanobis distance) of hoteling used in digital transformation and artificial intelligence tasks.
最適化:Optimization

Protected: Basic concept of anomaly and change detection – Neyman-Pearson Decision Rule

An Introduction to Machine Learning for Anomaly and Change Detection Used in Digital Transformation and Artificial Intelligence Tasks
地理空間情報処理

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.
グラフ理論

What is a Complex Network? A New Approach to Deciphering Complex Relationships Reading Memo

Overview of graph theory for analyzing complex network information used in artificial intelligence tasks (lattices and networks, Bacon and Erdesh numbers, small worlds, Beki rules, contagion transmission pathways, communication networks, neural networks, community networks).
C言語

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
微分積分:Calculus

Protected: MCMC method for calculating stochastic integrals: Algorithms other than Metropolis method (Gibbs sampling, MH method)

An overview of MCMC using Gibbs sampling and MH methods for probability integral computation for digital transformation and artificial intelligence task applications.
C言語

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.
微分積分:Calculus

Machine Learning Professional Series: Topic Models Post-Reading Notes

Topic models using probability generation models to extract sentence topics to be used in digital transformation (DX) and artificial intelligence (AI) tasks.
C言語

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
C言語

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
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