線形代数:Linear Algebra

Shaky Proteins and Old Me: Data Science in the Age of Misfolding

Integration of simulation and machine learning technologies used in digital transformation, artificial intelligence and machine learningtasks; application of simulation and machine learning PCA, RMA, canonical correlation analysis, independent component analysis, Bayesian inference, hidden Markov models) to protein functional analysis (misfolding, etc.

2022.06.08

IOT技術:IOT TechnologyStream Data Processingシミュレーション地理空間情報処理微分積分:Calculus推論技術:inference Technology時系列データ解析最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

Weather Forecasting and Data Science

Weather forecasting and data assimilation for simulation and data science integration for digital transformation, artificial intelligence, and machine learning task utilization

2022.06.01

IOT技術:IOT TechnologyStream Data Processingアルゴリズム:Algorithmsシミュレーションスパースモデリングデータベース技術:DataBase Technologyベイズ推定強化学習微分積分:Calculus推論技術:inference Technology時系列データ解析最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

Protected: Simulation, Data Assimilation, and Emulation

Fusion of extrapolation (deduction) estimation using simulation and interpolation (induction) estimation using machine learning (simulation assimilation and emulation using DNN, etc.) for digital transformation, artificial intelligence and machine learning tasks

2022.05.25

Stream Data Processingアルゴリズム:Algorithmsグラフ理論シミュレーション強化学習微分積分:Calculus時系列データ解析最適化:Optimization機械学習:Machine Learning深層学習:Deep Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

Encryption and security technologies and data compression techniques

Encryption, Security and Data Compression Technologies for Digital Transformation (DX) and Artificial Intelligence (AI) Tasks

2022.05.22

アルゴリズム:Algorithmsデータ圧縮/セキュリティ:Data compression and security線形代数:Linear Algebra

Protected: Time Series Data Analysis (1) – State Space Model

Overview of various state-space models linear and Gaussian state-space models, AR models, autoregressive and moving average ARMA models, component decomposition models, and time-varying coefficient models) for time series data analysis used in digital transformation, artificial intelligence, and machine learning tasks

2022.05.13

Stream Data Processingアルゴリズム:Algorithmsオンライン学習時系列データ解析最適化:Optimization機械学習:Machine Learning異常検知・変化検知線形代数:Linear Algebra

Structural Learning

About Structural Learning Learning the structure that data has is important for interpreting what the data is a...

2022.01.22

グラフ理論幾何学:Geometry微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

Machine Learning Professional Series “Continuous Optimization for Machine Learning” Reading Memo

Summary Continuous optimization in machine learning is a method for solving optimization problems in which varia...

2022.01.22

微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

Protected: Fundamentals of Online Learning Stochastic Gradient Descent – Application to Perceptron, SVM, and Logistic Regression

Online learning applications to the perceptron, SVM, and logistic regression for digital transformation , artificial intelligence , and machine learning tasks.

2022.01.06

オンライン学習微分積分:Calculus最適化:Optimization確率・統計:Probability and Statistics線形代数:Linear Algebra

Machine Learning Professional Series: Topic Models Post-Reading Notes

Topic models using probability generation models to extract sentence topics to be used in digital transformation (DX) and artificial intelligence (AI) tasks.

2021.11.28

微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

This is a good introduction to deep learning (Machine Learning Startup Series)Reading Notes

Overview of deep learning for digital transformation and artificial intelligence tasks, including machine learning, gradient descent, regularization, error back propagation, self-encoders, convolutional neural networks, recurrent neural networks, Boltzmann machines, and reinforcement learning.

2021.11.15

微分積分:Calculus数理論理学:Mathematical logic最適化:Optimization機械学習:Machine Learning深層学習:Deep Learning確率・統計:Probability and Statistics線形代数:Linear Algebra