推論技術:inference Technology Protected: Local features (1) Overview of local features and various filtering processes Overview of local feature extraction techniques and various filtering techniques in image recognition technology 2021.09.10 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
機械学習:Machine Learning Protected: Overview of Image Recognition (2) Overview of the treatment process Image recognition technology used in artificial intelligence (AI) and digital transformation (DX), specific recognition processes (class recognition, object recognition, instance recognition) 2021.09.09 機械学習:Machine Learning画像認識技術
推論技術:inference Technology Protected: Overview of Image Recognition (1) History and overview of image recognition technology History and overview of image recognition technology used in AI and DX 2021.09.08 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
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
R R language and Machine Learning Overview of the R language as a general-purpose tool for machine learning 2021.09.05 R推論技術:inference Technology機械学習:Machine Learning自然言語処理:Natural Language Processing
スパースモデリング Protected: Sparse Modeling and Multivariate Analysis (11) Practical Examples of SVD, PMD, and NMF with R Sparse Machine Learning, Matrix Decomposition (SVD, PMD, NMF) with R for Digital Transformation (DX), Artificial Intelligence (AI), Solid Line, BiocManager, PMA 2021.09.05 スパースモデリング機械学習:Machine Learning
スパースモデリング Protected: Sparse Modeling and Multivariate Analysis (10) Use of matrix data decomposition Machine learning for use in digital transformation (DX) and artificial intelligence (AI), application of matrix data analysis to sparse machine learning, SVD, PMD, NMF, LSA, LSI, PCA, LDA 2021.09.04 スパースモデリング機械学習:Machine Learning
スパースモデリング Protected: Sparse Modeling and Multivariate Analysis (9) Basics of Matrix Data Decomposition Machine learning techniques that can be used for digital transformation (DX) and artificial intelligence (AI), fundamentals of applying matrix data to machine learning, singularity decomposition, low-rank matrix approximation 2021.09.03 スパースモデリング機械学習:Machine Learning
検索技術:Search Technology Image Processing Technology Overview of image recognition technology used in artificial intelligence (AI) and digital transformation (DX) 2021.09.02 検索技術:Search Technology機械学習:Machine Learning深層学習:Deep Learning画像認識技術