確率・統計:Probability and Statistics

Protected: Graphical model with factor graph representation

An overview of factor graph models, a more generalized version of graphical models used in probabilistic generative models for digital transformation (DX), artificial intelligence (AI), and machine learning (ML) tasks

2022.06.29

アルゴリズム:Algorithmsグラフ理論ベイズ推定微分積分: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: Non-parametric Bayesian and clustering(1)Dirichlet distribution and infinite mixture Gaussian model

Analysis with a mixed Gaussian model that extends the Dirichlet distribution to infinite dimensions as a nonparametric Bayesian approach in stochastic generative models used in digital transformation artificial intelligence, and machine learning

2022.06.28

アルゴリズム:Algorithmsグラフ理論ベイズ推定微分積分:Calculus推論技術:inference Technology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集合論:Set theory

Protected: Overview of Gaussian Processes (1) Gaussian Processes and Kernel Tricks

Overview of the theory of Gaussian processes (support vector machines, related vector machines, RVMs, RBF kernels, kernel functions), which are dimensionless multivariate Gaussian distribution models with no specified parameters among stochastic generative models used in digital transformation, artificial intelligenceand machine learningtasks.

2022.06.27

アルゴリズム:Algorithmsグラフ理論ベイズ推定微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra集合論:Set theory

Introduction to Probability Theory Reading Notes

Introduction to Probability Theory Reading Notes From Introduction to Probability Theory 「It is said that...

2022.06.25

ベイズ推定数理論理学最適化:Optimization確率・統計:Probability and Statistics集合論:Set theory

Protected: Partitioning Method on Support Vector Machines (1) SMO Algorithm

Efficiency using the partitioning method (SMO algorithm) on support vector machines utilized for digital transformation (DX), artificial intelligence (AI), and machine learning (ML) tasks

2022.06.24

アルゴリズム:Algorithmsグラフ理論微分積分:Calculus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音声信号認識技術

Protected: Implementation of particle filter on time series data

Data assimilation using particle filters for time series data analysis utilized in digital transformation, artificial intelligence, and machine learning tasks and comparison of Kalman filter, particle filter (sequential Monte Carlo), and Markov chain Monte Carlo (MCMC) methods

2022.06.22

IOT技術:IOT TechnologyRStream Data Processingアルゴリズム:Algorithms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

134 Stories of Probability and Statistical Magic that Changed the World Reading Notes

134 Stories of Probability and Statistical Magic that Changed the World Reading Notes From Episode 134 of The Mi...

2022.06.18

確率・統計:Probability and Statistics

Protected: Introduction to Optimization with Support Vector Machines: Optimality Conditions and Generic Solution Methods

Optimality conditions (strong duality and KKT) and generic solution methods (active set and interior point method) in support vector machines used for digital transformation, artificial intelligence and machine learning tasks

2022.06.17

Symbolic Logicアルゴリズム:Algorithmsスパースモデリング最適化: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音声信号認識技術

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