微分積分:Calculus Machine Learning Professional Series Probabilistic Optimization Reading Notes
Summary
Stochastic optimization in machine learning will refer to the solution of optimization problems using r...
微分積分:Calculus
微分積分:Calculus アルゴリズム:Algorithms 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
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 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.
ベイズ推定 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...
アルゴリズム:Algorithms 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)
IOT技術:IOT Technology 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
アルゴリズム:Algorithms 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.
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
Stream Data Processing Protected: Simulation, Data Assimilation, and Emulation
Fusion of extrapolation (deduction) estimation using simulation and interpolation (induction) estimation using machine learning (simulation assimilation and emulation using DNN, etc.) for digital transformation, artificial intelligence and machine learning tasks