微分積分:Calculus

Protected: State Space Modeling with R – using dlm and KFAS (3) Analysis with KFAS

Time series data analysis for digital transformation, artificial intelligence, and machine learning tasks; examples of time series analysis on real data using KFAS in R normal distribution, Poisson distribution, Kalman filter, first-order difference model, second-order difference model

2022.06.16

IOT技術:IOT TechnologyRStream Data Processing微分積分:Calculus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

Dream of a realistic SimCity

Integration of simulation and machine learning technologies used for digital transformation, artificial intelligence, and machine learning tasks; application of SimCity to the real world using emulation and machine learning

2022.06.15

アルゴリズム:Algorithmsグラフ理論コンピューターシミュレーション微分積分:Calculus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

Machine Learning Professional Series Probabilistic Optimization Reading Notes

Summary Stochastic optimization in machine learning will refer to the solution of optimization problems using r...

2022.06.11

微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics

Protected: kernel function

General kernel functions in support vector machines used in digital transformation (DX), artificial intelligence (AI), and machine learning, and kernel functions on probabilistic, string, and graph-type data

2022.06.10

アルゴリズム:Algorithmsグラフ理論微分積分:Calculus推論技術:inference Technology最適化:Optimization機械学習:Machine Learning画像認識技術異常検知・変化検知確率・統計:Probability and Statistics音声信号認識技術

Protected: State space modeling with R – using dlm and KFAS (2) Seasonal adjustment model with dlm

Analysis of time series data used for digital transformation (DX), artificial intelligence (AI), and machine learning (ML) tasks, and seasonal-variant time series models on real data using R's dlm

2022.06.09

RStream Data Processingアルゴリズム:Algorithms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非同期/並行処理:Asynchronous/parallel processing

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

Machine Learning Professional Series Statistical Learning Theory Reading Notes

Summary The theory of statistical properties of machine learning algorithms can be used to theoretically elucid...

2022.06.04

ベイズ推定微分積分:Calculus推論技術:inference Technology数理論理学:Mathematical logic最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics

Protected: Support vector machines for unsupervised learning

Application of support vector machines for digital transformation, artificial intelligence, and machine learning tasks (1-class SVM with nu-SV classification algorithm for unsupervised classification used for anomaly detection)

2022.06.03

アルゴリズム:Algorithmsグラフ理論微分積分:Calculus数理論理学:Mathematical logic最適化:Optimization機械学習:Machine Learning画像認識技術確率・統計:Probability and Statistics自然言語処理:Natural Language Processing

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: Regression Analysis with Support Vector Machines (2) Approach to Nonlinear Regression Problems

Approaches to nonlinear regression problems with support vector machines (quantile regression, kernel quantile regression, heterogeneous distribution models, ε-insensitive loss functions) utilized in digital transformation, artificial intelligence, and machine learning tasks.

2022.05.27

アルゴリズム:Algorithms幾何学:Geometry微分積分:Calculus最適化:Optimization機械学習:Machine Learning画像認識技術自然言語処理:Natural Language Processing関係データ学習音声信号認識技術