自然言語処理:Natural Language Processing

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.
機械学習:Machine Learning

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.
機械学習:Machine Learning

Protected: Language Models in Speech Recognition

Language models (n-gram models and probabilistic models) used in speech recognition for digital transformation and artificial intelligence tasks.
機械学習:Machine Learning

Dealing with the meaning of symbols on a computer

An overview of the steps to handle the meaning of symbols in computers used for digital transformation and artificial intelligence tasks.
python

Python and Machine Learning(3)Other Machine Learning

Overview of Python, a programming language used in digital transformation , artificial intelligence , and machine learning
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
機械学習:Machine Learning

Deep Learning Technologies

Deep learning technology, one of the breakthroughs in artificial intelligence technology and machine learning technology
推論技術:inference Technology

Overview of Kernel Methods and Support Vector Machines

On kernel methods, one of the breakthroughs in machine learning technology
推論技術:inference Technology

Protected: Classification (4) Group learning(Ensemble Learning, Random Forest) and evaluation of learning results(Cross-validation method)

Algorithms for collective learning for data classification and evaluation of classification results (ensemble learning, bagging, boosting, random forests, cross-validation)
R

R language and Machine Learning

Overview of the R language as a general-purpose tool for machine learning
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