Analysis

中国古典:classics

Sun Tzu’s approach has its roots in problem-solving methods.

Sun Tzu's ideas, which are the roots of problem-solving methods (100 victories in 100 battles, advance planning, winning without fighting, five things and seven plans, mausoleum calculation, analysis, objective, visualization)
Clojure

Protected: Analysis of time series data using Clojure

Analysis of time series data such as AR, MA, ARMA, etc. using Clojure for digital transformation, artificial intelligence machine learning tasks ACF, PACF, Partial Autocorrelation, Durbin-Levinson algorithm, autocovariance, moving average models, autocorrelation models, hybrid, random walk, discrete-time models
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
R

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
IOT技術:IOT Technology

Protected: State Space Modeling with R – using dlm and KFAS (1) Basic analysis using dlm

Analysis using dlm on real data (quarterly sales volume data of products) in the analysis of time-series data (on data prediction and filtering and smoothing) used in digital transformation, artificial intelligence , and machine learning tasks.
IOT技術:IOT Technology

Protected: Time series data analysis (3)Filtering of nonlinear and non-Gaussian state space models (e.g. particle filter)

Filtering and smoothing of nonlinear and non-Gaussian state-space models using particle filters in the analysis of time-series data with state-space models for digital transformation, artificial intelligence, and machine learning tasks
IOT技術:IOT Technology

Protected: Time series data analysis (2) Filtering Sequential estimation of state and seasonal adjustment model

Prediction of time series using state-space models of time series data utilized in digital transformation, artificial intelligence, and machine learning; interpolation, parameter estimation, and analysis of store sales using component decomposition and standard seasonal adjustment models.
Symbolic Logic

Protected: Causal InferenceIntroduction(2)Stratified Analysis and Regression Modeling

Theory and practice of causal inference through analysis by stratified analysis and regression models for statistical causal estimation used in digital transformation , artificial intelligence , and machine learning tasks
Symbolic Logic

Graph data processing algorithms and their application to Machine Learning and Artificial Intelligence tasks

Theory, implementation, and use of algorithms for analyzing graph data.
機械学習:Machine Learning

Protected: Higher-order relational data – an overview of tensor data processing

Tensor data processing to analyze relationships between three or more objects for use in digital transformation and artificial intelligence tasks.
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