線形代数:Linear Algebra

アルゴリズム:Algorithms

Protected: Overview of Gaussian Processes(3)Gaussian Process Regression Model

Computation and optimization of regression models and predictive distributions using Gaussian processes, which are dimensionless stochastic generative models used in digital transformation, artificial intelligence, and machine learning tasks
2022.07.11
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数理論理学:Mathematical logic最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra
微分積分:Calculus

Intuitive Methods in Economic Mathematics: Probability and Statistics Reading Notes

  Summary Economic mathematics is the study of mathematical methods of analysis in economics. It refers to the a...
2022.07.09
微分積分:Calculus最適化:Optimization確率・統計:Probability and Statistics線形代数:Linear Algebra
IOT技術:IOT Technology

Protected: Causal Inference with VAR Model (1) Interpolation of missing data and DF and ADF tests

Overview of multivariate autoregressive models for finding causal relationships between two time series data in time series data analysis using state space models for digital transformation, artificial intelligence, and machine learning tasks, and completion of missing data using R and DF and ADF tests
2022.07.07
IOT技術:IOT TechnologyStream Data Processing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
アルゴリズム:Algorithms

Protected: Calculation of marginal probability distributions – Probability Propagation Method

Compute the probability distribution around graphical models in probabilistic generative models used in digital transformation, artificial intelligence , and machine learning tasks, such as Bayesian estimation, using probability propagation methods
2022.07.06
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
アルゴリズム:Algorithms

Various probability distributions

Overview of various probabilistic models used as approximate models for probabilistic generative models utilized in digital transformation, artificial intelligence, and machine learning tasks (Student's t distribution, Wishart distribution, Gaussian distribution, gamma distribution, inverse gamma distribution, Dirichlet distribution, beta distribution, categorical distribution, Poisson distribution, Bernoulli distribution)
2022.07.05
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
アルゴリズム:Algorithms

Protected: Overview of Gaussian Processes(2)Gaussian Processes and Kernels

Gaussian processes and kernel functions (Mattern kernel, character kernel, Fisher kernel, HMM's marginalized kernel, linear kernel, exponential kernel, periodic kernel, RBF kernel), which are dimensionless stochastic generative models used for digital transformation, artificial intelligence and machine learning tasks
2022.07.04
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確率・統計:Probability and Statistics線形代数:Linear Algebra
幾何学:Geometry

Nine Stories of Probability and Statistics That Changed Humans and Society Reading Notes

Nine Stories of Probability and Statistics That Changed Humans and Society Reading Notes From Nine Stories of Pr...
2022.07.02
幾何学:Geometry微分積分:Calculus確率・統計:Probability and Statistics線形代数:Linear Algebra
アルゴリズム:Algorithms

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
アルゴリズム:Algorithms

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
アルゴリズム:Algorithms

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
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