ICT技術:ICT Technology

Protected: Microservices Architecture

The ideal enterprise system would be tightly integrated and provide all business functions as a single unit optimized for a particular technology stack and hardware. Such monolithic systems often become more complex over time and difficult to understand as a single unit by a single team. Domain-driven design advocates decomposing such systems into smaller modular components and assigning them to teams that focus on a single business capability in a limited context.

2022.09.05

web技術:web technologyアーキテクチャコンピューターデータベース技術:DataBase Technology

Thinking Machines Machine Learning and its Hardware Implementation

Summary Many hardware implementations of machine learning are dedicated hardware. These means include the f...

2022.09.03

コンピューターハードウェア機械学習:Machine Learning

Protected: Support Vector Machines for Weak Label Learning (2) Multi-Instance Learning

Extension of support vector machines utilized for digital transformation, artificial intelligence, and machine learning tasks; multi-instance learning approach with SVMs for weak-label learning problems (mi-SVM, MI-SVM)

2022.09.02

アルゴリズム:Algorithmsグラフ理論微分積分:Calculus最適化:Optimization機械学習:Machine Learning画像認識技術異常検知・変化検知確率・統計:Probability and Statistics線形代数:Linear Algebra自然言語処理:Natural Language Processing音声信号認識技術

Integration of Clojure with Javascript and node.js and web frameworks

Implementation of Clojure integration with web frameworks (javascript, React, node.js, etc.) used for digital transformation and artificial intelligence tasks using Clojurescript

2022.08.26

Clojurejavascriptweb技術:web technology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 and Python integration and machine learning

Implementation of a library (libpython-clj) and sample code (transformers, lime, autoencoder, etc.) for integration with Clojure for Python modules used for digital transformation, artificial intelligence and machine learning tasks

2022.08.25

ClojurepythonRアルゴリズム:Algorithms数学:Mathematics機械学習:Machine Learning

GPy – A Python-based framework for Gaussian processes

GPy Gaussian regression problem, auxiliary variable method, sparse Gaussian regression, Bayesian GPLVM, latent variable model with Gaussian processes, a Python-based implementation of Gaussian processes, an application of stochastic generative models used in digital transformation, artificial intelligence and machine learning tasks.

2022.08.24

pythonアルゴリズム:Algorithmsスパースモデリングスパースモデリング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 of Gaussian Processes in Clojure

Implementation of Gaussian processes in Clojure using fastmath as an extension of stochastic generative models utilized in digital transformation, artificial intelligence, and machine learning tasks

2022.08.23

ClojureJavaアルゴリズム:Algorithmsスパースモデリング微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

Python development environment in SublimeText4

Launch of Python development environment in SublimeText4 and VS code for digital transformation (DX), artificial intelligence (AI) and machine learning (ML) tasks

2022.08.22

pythonテキストウディタ

Setting up a Clojure development environment with SublimeText4 and VS code and LightTable

Launch of development environment in Sublimetext and VS code for Clojure language used for digital transformation (DX), artificial intelligence (AI) and machine learning (ML) tasks

2022.08.22

Clojureテキストウディタ

Protected: Support Vector Machines for Weak Label Learning (1) Semi-supervised Learning

Weak label learning (semi-supervised learning where label information is given only for a subset of training cases) as an application of support vector machines utilized in digital transformation, artificial intelligence, and machine learning tasks

2022.08.19

アルゴリズム:Algorithms微分積分:Calculus数理論理学最適化:Optimization機械学習:Machine Learning画像認識技術異常検知・変化検知確率・統計:Probability and Statistics線形代数:Linear Algebra自然言語処理:Natural Language Processing音声信号認識技術