数学:Mathematics

アルゴリズム:Algorithms

Protected: Gaussian Processes – The Advantages of Functional Clouds and Their Relationship to Regression Models, Kernel Methods, and Physical Models

Gaussian Processes as Applications of Stochastic Generative Models for Digital Transformation (DX), Artificial Intelligence (AI), and Machine Learning (ML) Tasks Miscellaneous Function Clouds Advantages and Regression Models and their Relationship to Kernel Methods and Physical Models
R

Protected: Structured Support Vector Machines

SVM structure learning and parsing using the deletion plane method algorithm on support vector machines utilized for digital transformation, artificial intelligence, and machine learning tasks, and protein similarity sequence search
グラフ理論

Optimization for the First Time Reading Notes

Optimization for the First Time Reading Notes From Optimization for Beginners This book is explained in d...
アルゴリズム:Algorithms

Protected: About Bayesian Statistics and Machine Learning

The impact of machine learning on scientific methodology and engineering, and the suitability of probabilistic statistical approaches, particularly Bayesian models, for machine learning design
アルゴリズム:Algorithms

The Impact of Blockchain: A Disruptive Technology that is Overturning the Social Structure from Bitcoin, FinTech to IoT – Reading Notes

Mathematics  Machine Learning Technology  Artificial Intelligence Technology  Algorithm  Digital Transformation Technolo...
アルゴリズム:Algorithms

Algorithm Introduction

Summary An algorithm represents a process that takes input, processes it in some procedure, and finally return...
アルゴリズム:Algorithms

Protected: Support vector machine software and implementation

Classification and regression with SVM using R kernlab in support vector machines used for digital transformation, artificial intelligence and machine learning tasks and LIBSVM algorithms SMO algorithm, shrinking
アルゴリズム:Algorithms

Protected: Computing Peripheral Probability Distributions – Mean Field Approximation

Application of graphical models to stochastic generative models utilized in digital transformation, artificial intelligence, and machine learning tasks; approximate computation and algorithms for peripheral probability distributions from variational problems using mean field approximation
アルゴリズム:Algorithms

Protected: Variational Bayesian Learning Framework and Algorithms

Overview of variational Bayesian learning and algorithms (variational Bayesian learning, empirical variational Bayesian learning) for approximate computation of complex models in stochastic generative models used in digital transformation, artificial intelligence, and machine learning tasks.
アルゴリズム:Algorithms

Protected: Comparison of clustering using k-means and Bayesian estimation methods (mixed Gaussian model)

Comparison of k-means and Bayesian estimation (mixed Gaussian model) clustering as probabilistic generative models utilized in digital transformation, artificial intelligence , and machine learning tasks
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