Causality

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

Protected: Quasi-experimental design – how to derive causal relationships from observed data

How to verify causality for digital transformation, artificial intelligence , and machine learning tasks by first having the data for causal inference and then verifying causality from there.

2022.03.25

Symbolic Logicグラフ理論推論技術:inference Technology数理論理学機械学習:Machine Learning確率・統計:Probability and Statistics関係データ学習

Protected: Discrepancy between correlation (regression coefficient) and causation (intervention effect)

Differences between regression coefficients and intervention effect values for digital transformation, artificial intelligence , and machine learning tasks.

2022.03.22

Symbolic Logicグラフ理論推論技術:inference Technology数理論理学最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics関係データ学習

Protected: Introduction to Causal Inference (1) Confounding Factors and Randomized Experiments

Introduction to statistical causal inference (randomized experiments controlling for confounding factors to distinguish between causality and pseudo-correlation)

2022.03.17

Symbolic Logicグラフ理論推論技術:inference Technology数理論理学最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics

Causality, Zen, and Philosophy

The Zen way of thinking about cause and effect, and the philosophy of life tips

2021.03.17

哲学:philosophy禅:Zen