DX | Page 17 | Deus Ex Machina

Protected: Calculation method for Gaussian processes based on a lattice arrangement of auxiliary points

Gaussian process method calculations based on lattice-like auxiliary point arrangements in Gaussian process models Kronecker method, Teblitz method, local kernel interpolation, KISS-GP method, an application of stochastic generative models used in digital transformation, artificial intelligence, machine learning

2022.10.24

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

About Boot, Clojure’s other development environment

About Boot, Clojure's development framework used for digital transformation (DX), artificial intelligence (AI), and machine learning (ML) tasks

2022.10.21

Clojureweb技術:web technology

Implementing a REST API for Microservices with Clojure using Pedestal

Implementation of a flexible REST API for microservices with Clojure using Pedestal for digital transformation (DX) and artificial intelligence (AI) tasks.

2022.10.20

web技術:web technologyネットワーク技術

State Space Model with Clojure: Implementation of Kalman Filter

State space models using Clojure for digital transformation (DX), artificial intelligence (AI), and machine learning (ML) tasks: implementation of Kalman filter

2022.10.19

ClojureIOT技術:IOT Technologyアルゴリズム:Algorithmsベイズ推定微分積分:Calculus機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

Protected: Analysis of time series data using Clojure

Analysis of time series data such as AR, MA, ARMA, etc. using Clojure for digital transformation, artificial intelligence machine learning tasks ACF, PACF, Partial Autocorrelation, Durbin-Levinson algorithm, autocovariance, moving average models, autocorrelation models, hybrid, random walk, discrete-time models

2022.10.18

Clojureアルゴリズム:Algorithms微分積分:Calculus時系列データ解析最適化: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

Analysis in R and Clojure using Stan for Markov Chain Monte Carlo (MCMC) models

Implementation using R and Clojure of Stan, a computational tool using MCMC for Bayesian estimation used in digital transformation, artificial intelligence, and machine learning tasks.

2022.10.17

ClojureR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

Java, Scala and Koltlin, general-purpose application building environments

Java, Scala and Koltlin, general-purpose application building environments used for digital transformation (DX), artificial intelligence (AI) and machine learning (ML) tasks

2022.10.16

ClojureJavaKoltlin

Protected: Machine Translation Today and Tomorrow – Different Machine Learning Approaches for Natural Language

Present and future of machine translation for digital transformation, artificial intelligence, and machine learning tasks - Different machine learning approaches for natural language machine translation based on attentional neural nets, machine translation based on encoding and decoding, recurrent neural nets, machine translation based on neural nets and neural models, neural net-based translation, tree-to-strong translation, pre-ordering, parse trees and parsing, word mapping, phrase-based translation

2022.10.15

アルゴリズム:Algorithmsグラフ理論ベイズ推定最適化: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自然言語処理:Natural Language Processing

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