digital transformation

Protected: Overview of model-based approach to reinforcement learning and its implementation in python

Overview of reinforcement learning with model-based approaches used for digital transformation, artificial intelligence, and machine learning tasks and its implementation in python Bellman Equation, Value Iteration, Policy Iteration

2022.10.14

pythonアルゴリズム:Algorithmsオンライン学習強化学習微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

Protected: Bayesian Learning and Conjugacy

Conjugacy of various probability functions (Gaussian, Bernoulli, Poisson, Dirichlet, and Gamma distributions) and prior distributions for Bayesian learning calculations in stochastic generative models utilized in digital transformation, artificial intelligence, and machine learning tasks

2022.10.13

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

Protected: Nonparametric Bayes from the viewpoint of point processes – Poisson and gamma processes

Nonparametric Bayes from the viewpoint of point processes as an application of stochastic generative models used in digital transformation, artificial intelligence, and machine learning tasks - Poisson and gamma processes additive processes, Poisson random measures, gamma random measures, discreteness, Laplace functional, point processes

2022.10.11

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集合論:Set theory

Protected: Computational Methods for Gaussian Processes(2)Variational Bayesian Method and Stochastic Gradient Method

Calculations using variational Bayesian and stochastic gradient methods for Gaussian process models, an application of stochastic generative models utilized in digital transformation, artificial intelligence, and machine learning tasks Kullback-Leibler information content, Jensen inequality, evidence lower bound function, mini-batch method, evidence lower bound, variational posterior distribution, evidence variational lower bound

2022.10.10

アルゴリズム:Algorithmsグラフ理論スパースモデリング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

Overview and installation of nginx server

Overview and installation of nginx servers used for digital transformation (DX), artificial intelligence (AI), and machine learning (ML) tasks

2022.10.07

web技術:web technology

Implementation of hidden Markov model with Viterbi algorithm and stochastic generative model using Clojure

Implementation of hidden Markov models with Viterbi algorithm and probabilistic generative models using Clojure for digital transformation, artificial intelligence, and machine learning tasks

2022.10.06

Clojure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集合論:Set theory

Implementation in Clojure of streaming data processing for IOT, Stock Data Analysis

Implementation of core.async asynchronous applications using Clojure such as IOT and stock data analysis for digital transformation (DX), artificial intelligence (AI) and machine learning (ML) tasks

2022.10.05

ClojureIOT技術:IOT TechnologyStream Data Processing

Implementation of a simple recommendation algorithm using Clojure

Implementation of a simple recommendation algorithm (slope-one algorithm) using Clojure for digital transformation (DX), artificial intelligence (AI), and machine learning tasks

2022.10.04

Clojure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

Chinese resturant process (CRP) using Clojure and its application to mixed Gaussian distributions

Application to the Chinese resturant process (CRP) and mixed Gaussian distribution using Clojure for probabilistic generative models used in digital transformation, artificial intelligence, and machine learning tasks

2022.10.03

Clojure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集合論:Set theory

Protected: Equivalence of neural networks (deep learning) and Gaussian processes

On the equivalence of Gaussian processes and neural networks, an applied model of stochastic generative models used in digital transformation, artificial intelligence, and machine learning tasks from Neal's paper

2022.10.01

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深層学習:Deep Learning確率・統計:Probability and Statistics線形代数:Linear Algebra