LISP The Little Schemer A textbook on functional languages in Schema, a derivative of LISP used for AI tasks (recursion and anonymous functions, lambda functions, Y-combinators and a simple interpreter). 2021.10.17 LISPSymbolic Logicエキスパートシステム:expertsystem推論技術:inference Technology自然言語処理:Natural Language Processing
python Protected: Introduction to programming in the Python language (2) Characteristics of the Python language Table of contents for the MIT Python textbook and features of the Python language used for digital transformation (DX) and artificial intelligence (AI) tasks. 2021.10.17 python機械学習:Machine Learning
prolog The Art of Prolog A reference book on Prolog, a logic programming language with deep connections to artificial intelligence research and computational linguistics. 2021.10.16 prolog推論技術:inference Technology
IOT技術:IOT Technology Protected: An Invitation to Spatial Epidemiology – What can we see from the map of intractable diseases? Geographic information analysis for epidemiology using Poisson-Gamma model, CDT and scan statistic test for digital transformation and artificial intelligence tasks. 2021.10.16 IOT技術:IOT Technology地理空間情報処理推論技術:inference Technology機械学習:Machine Learning確率・統計:Probability and Statistics
IOT技術:IOT Technology Protected: Introduction to Customer Motivation Research HMM, k-medoids, and kernel density estimation for customer flow analysis used in digital transformation and artificial intelligence tasks. 2021.10.15 IOT技術:IOT Technology地理空間情報処理機械学習:Machine Learning
python A Textbook of Algorithms in Python Python's Programming Basics and Algorithm Implementation Reference Book 2021.10.11 pythonアルゴリズム:Algorithms
機械学習:Machine Learning Protected: Capturing “Individuality” with Hierarchical Models (Hierarchical Bayesian Models and Empirical Bayesian Methods (GLMM)) Understanding "personality" in hierarchical Bayesian models and solving with empirical Bayesian methods (GLMM), which can be used for artificial intelligence (AI), natural language processing, and digital transformation (DX). 2021.10.11 機械学習:Machine Learning確率・統計:Probability and Statistics
機械学習:Machine Learning Protected: Applying Deep Learning to Speech Recognition Overview of neural network applications (TDNN, RNN, CNN) and deep learning applications (LSTM, CTC) for speech recognition technology used in digital transformation and artificial intelligence tasks 2021.10.07 機械学習:Machine Learning深層学習:Deep Learning音声信号認識技術
推論技術:inference Technology Concrete and Abstract – natural language sematics and explain Concrete and abstract to consider the meaning of natural language and explainable machine learning that can be used for digital transformation and artificial intelligence tasks. 2021.10.06 推論技術:inference Technology機械学習:Machine Learning自然言語処理:Natural Language Processing
機械学習:Machine Learning Protected: Speaker adaptation and speaker recognition Speaker adaptation (HMM) to improve recognition accuracy for digital transformation and artificial intelligence tasks, and speaker recognition (maximum likelihood linear regression, MLLR, i-vector) for security and other applications. 2021.10.05 機械学習:Machine Learning確率・統計:Probability and Statistics音声信号認識技術