artificial intelligence

数理論理学:Mathematical logic

Overview of Set Theory and Reference Books

What are sets for digital transformation, artificial intelligence, and machine learning task utilization for first-time learners Cantor's set theory, intuitionistic logic, quantum logic, topological spaces, Grothendieck, Goeter, Cohen, unreachable numbers, measurable numbers, axiom of determination, Frenkel's substitution axiom, von Neumann's regularity axiom, axiomatic set theory, BG set theory, Zermelo set theory, Cantor's diagonal theory reading notes
web技術:web technology

REST API for Microservices Overview

REST API and RESTful services, key elemental technologies of microservices used for digital transformation and artificial intelligence tasks
アルゴリズム:Algorithms

Protected: Overview and history of the banded problem and its relationship to reinforcement learning/online learning

Overview and history of bandit problems utilized in digital transformation, artificial intelligence, and machine learning tasks and their relationship to reinforcement learning online learning
アルゴリズム:Algorithms

Protected: Application of Variational Bayesian Algorithm to Mixed Gaussian Distribution Models

Application of variational Bayesian algorithms to mixed Gaussian distribution models for the computation of stochastic generative models utilized in digital transformation, artificial intelligence, and machine learning tasks (Dirichlet distribution, isotropic Gaussian distribution, free energy calculation)
アルゴリズム:Algorithms

Protected: Specific examples of graphical models

Computation of specific graphical models such as Boltzmann Machines, Mean Field Approximation, Bethe Approximation, Hidden Markov Models, Bayesian Hidden Markov Models, etc. as probabilistic generative models utilized in digital transformation, artificial intelligence and machine learning tasks.
アルゴリズム:Algorithms

Protected: Nonparametric Bayesian Applications to Factor Analysis and Sparse Modeling

Nonparametric Bayesian models, one of the applications of probabilistic generative models utilized in digital transformation, artificial intelligence, and machine learning tasks, for factor analysis and sparse modeling (infinite latent feature model, beta-Bernoulli distribution model, Indian cuisine buffet process, binary matrix generation process)
アルゴリズム:Algorithms

Protected: Stochastic Generative Models and Gaussian Processes(3) Representation of Probability Distributions

Stochastic generative models utilized in digital transformation, artificial intelligence, and machine learning tasks and representation of probability distributions in samples as a basis for Gaussian processes ,weighted sampling, kernel density estimation, distribution estimation using neural nets
Clojure

Implementation of a Bayesian optimization tool using Clojure

Introduction of Clojure implementation of Bayesian optimization tool, a (hyperparameter) optimization tool used for digital transformation (DX), artificial intelligence (AI), and machine learning (ML) tasks, and opimx, an optimization comparison tool in R.
Clojure

Chatbot implementation using Clojure and Javascript and integration of AI functionality

Building a chatbot framework in Clojure and Javascript for use in digital transformation , artificial intelligence , and machine learning tasks and integrating various AI functions natural language processing, SVM, BERT, Transformer, Knowledge Graph, database, expert systems
Clojure

Statistical learning by linking Clojure and R

Use of R with Clojure, a statistical machine learning library used for digital transformation (DX), artificial intelligence (AI), and machine learning (ML) tasks (Clojisr, Rojure, Rincanter, Huri, clj-iri, graalvm-interop, gg4clj, FastR, Rserve, Java)
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