機械学習:Machine Learning

Protected: Individuality and parameter estimation (Interpreting the Hierarchical Bayesian Model)

Relationship between global parameter estimation and local parameters (e.g., individual differences) for understanding hierarchical Bayesian models.

2021.10.19

推論技術:inference Technology機械学習:Machine Learning確率・統計:Probability and Statistics

Protected: Capturing the Flu Epidemic on Social Media

Extraction of context (e.g., location information) from text information in social media for digital trasformation and artificial intelligence tasks (location information extraction from content using probabilistic framework and graph approach)

2021.10.18

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自然言語処理:Natural Language Processing

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

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

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

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

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

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

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

Protected: Instance recognition and retrieval (1) Instance retrieval using BoVW

Instance recognition and image retrieval technology based on image recognition technology used in digital transformationand artificial intelligence

2021.10.04

推論技術:inference Technology検索技術:Search Technology機械学習:Machine Learning深層学習:Deep Learning画像認識技術