確率・統計:Probability and Statistics

Protected:

Overview of noise reduction techniques to improve speech recognition for digital transformation and artificial intelligence tasks (additive noise, multiplicative noise and active noise control, parallel model coupling, PMC, factorial HMM)

2021.10.03

機械学習:Machine Learning深層学習:Deep Learning確率・統計:Probability and Statistics音声信号認識技術

Protected: Large-vocabulary continuous speech recognition

Overview of large-vocabulary continuous speech recognition, a technology for recognizing unconstrained general speech in speech recognition technology used for digital transformation and artificial intelligence tasks.

2021.10.02

機械学習:Machine Learning確率・統計:Probability and Statistics自然言語処理:Natural Language Processing音声信号認識技術

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

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

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

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

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

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

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

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