機械学習:Machine Learning Protected: From Averages to Individuality: The Open World of Statistical Modeling (2)hierarchical Bayesian model From the Statistics of Means to the Statistics of Individuality Estimation with Bayesian Modeling 2021.09.23 機械学習:Machine Learning確率・統計:Probability and Statistics
機械学習:Machine Learning Protected: From Averages to Individuality: The Open World of Statistical Modeling (1)Statistical Model Overview From statistics of averages to statistics of personality, using Bayesian modeling, Hierarchical Bayes 2021.09.22 機械学習:Machine Learning確率・統計:Probability and Statistics
推論技術:inference Technology Protected: Introduction to Hierarchical Bayes (from GLM to Hierarchical Bayesian Model) Bayesian inference that can be used for artificial intelligence (AI), natural language, and digital transformation (DX); generate hierarchical Bayesian models from GLM models to solve complex statistical models 2021.09.21 推論技術:inference Technology機械学習:Machine Learning確率・統計:Probability and Statistics自然言語処理:Natural Language Processing
推論技術:inference Technology Protected: What is MCMC (Overview) Markov Chain Monte Carlo (MCMC), a key tool in Bayesian inference for artificial intelligence (AI) tasks, digital transformation (DX), natural language processing, etc. 2021.09.07 推論技術:inference Technology最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics
推論技術:inference Technology Protected: Bayesian Super Quick Learning (Basics of Bayesian Estimation and Hierarchical Bayesian Models) The basics of Bayesian inference and hierarchical Bayesian models that can be used for various tasks, including state space models, hidden Markov models, Markov field models, and CAR models. 2021.09.06 推論技術:inference Technology機械学習:Machine Learning確率・統計:Probability and Statistics
機械学習:Machine Learning Protected: Topic models that capture the individuality of language Topic models to capture latent meanings behind sentences, differences between various probabilistic approaches and deep learning, supervised LDA, Boltzmann machines,Naive Bayes 2021.08.26 機械学習:Machine Learning確率・統計:Probability and Statistics自然言語処理:Natural Language Processing
確率・統計:Probability and Statistics Introduction to models of language (probabilistic unigram models and Bayesian probability) Natural language processing as it applies to digital transformation (DX), artificial intelligence (AI), machine learning, etc. Modeling of natural language, application of unigram models and Bayesian probabilistic models. 2021.08.25 確率・統計:Probability and Statistics自然言語処理:Natural Language Processing
IOT技術:IOT Technology Protected: Analysis of Time Series Data (4) ARCH Model and GARCH Model Basic analysis of time series data used in digital transformation (DX), machine learning (ML), artificial intelligence (AI), and IOT, and ARCH and GARCH models 2021.08.03 IOT技術:IOT TechnologyStream Data Processing推論技術:inference Technology機械学習:Machine Learning確率・統計:Probability and Statistics
セマンテックウェブ技術:Semantic web Technology Protected: Analysis of Time Series Data (3) Analysis of Time Dependent Data and AR Model Basic analysis of time series data used in digital transformation (DX), machine learning (ML), artificial intelligence (AI), and IOT, AR models, random walks, and white noise 2021.08.02 セマンテックウェブ技術:Semantic web Technology推論技術:inference Technology機械学習:Machine Learning確率・統計:Probability and Statistics
推論技術:inference Technology Heuristics and Frame Problems Heuristics and artificial intelligence frame problems at the base of human behavior.macro-economics 2021.07.31 推論技術:inference Technology確率・統計:Probability and Statistics課題解決:Problem solving