ML

javascript

BotMan, a production-oriented chatbot system using PHP/Laravel

Overview of open source chatbot systems used for digital transformation, artificial intelligence, and machine learning tasks and implementation of BotMan, a production-oriented chatbot system using PHP/Laravel
2022.09.21
javascriptエキスパートシステム:expertsystemチャットボットマルチエージェントシステムユーザーインターフェース/データビジュアライゼーション
Clojure

Probabilistic Programming with Clojure

Probabilistic programming with Clojure.Anglican utilized for digital transformation, artificial intelligence, and machine learning tasks gorilla-repl, Stan, BUGS, Picture, Turing, Gen, PyStan PyMC, pomegranater, Lea, bayesloop, Edward, Tensorflow Probability, Pyro, BLOG, Dyna, ProbLog, Church, Anglican, Distributions
2022.09.20
ClojureJavaprologpythonRアルゴリズム:Algorithmsベイズ推定微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra
Symbolic Logic

Modeling that combines probability and logic (2) PLL (Probabilistic Logical Learning)

Fusion modeling of probability and logic Probabilistic Logical Learning, ILP, PRISM used for digital transformation, artificial intelligence, and machine learning tasks.
2022.09.19
Symbolic Logicアルゴリズム:Algorithmsエキスパートシステム:expertsystemグラフ理論シミュレーションベイズ推定微分積分:Calculus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線形代数:Linear Algebra集合論:Set theory
アルゴリズム:Algorithms

Protected: Replica Exchange Monte Carlo and Multicanonical Methods

On replica exchange Monte Carlo and multi-canonical methods, which are algorithms to avoid falling into local solutions in Markov chain Monte Carlo methods used for digital transformation, artificial intelligence, and machine learning tasks.
2022.09.18
アルゴリズム:Algorithmsグラフ理論ベイズ推定幾何学:Geometry微分積分:Calculus数理論理学:Mathematical logic最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra集合論:Set theory
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
2022.09.18
数理論理学:Mathematical logic集合論:Set theory
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
2022.09.16
アルゴリズム:Algorithmsバンディッド問題強化学習機械学習:Machine Learning深層学習:Deep 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)
2022.09.15
アルゴリズム:Algorithmsベイズ推定微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra
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.
2022.09.14
アルゴリズム:Algorithmsグラフ理論ベイズ推定微分積分:Calculus推論技術:inference Technology最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra
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)
2022.09.13
アルゴリズム:Algorithmsグラフ理論ベイズ推定微分積分:Calculus推論技術:inference Technology最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra集合論:Set theory
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
2022.09.12
アルゴリズム:Algorithmsグラフ理論ベイズ推定微分積分:Calculus推論技術:inference Technology最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra
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