machine learning

Clojure

Protected: Stochastic gradient descent implementation using Clojure and Hadoop

Stochastic gradient descent implementation using Clojure and Hadoop for digital transformation, artificial intelligence, and machine learning tasks (mini-batch, Mapper, Reducer, Parkour, Tesser, batch gradient descent, join-step Partitioning, uberjar, Java, batch gradient descent, stochastic gradient descent, Hadoop cluster, Hadoop distributed file system, HDFS)
アルゴリズム:Algorithms

Implementation of Neural Networks and Error Back Propagation using Clojure

Implementation of neural nets and error back propagation using Clojure for digital transformation (DX), artificial intelligence (AI), and machine learning (ML) tasks
Clojure

Use of ElasticStash for monitoring system operations, including microservices

Leveraging ElasticStash for system operations monitoring, including microservices leveraged for digital transformation artificial intelligence, and machine learning tasks Riemann, rollup, throttle structure, KafKa plugin, UTC, timbre LogStash, log4j, tools.logging, structured logging, common log formats, visualization features, dashboards, Kibana, pipeline, UDP, Collectd, RRD, stdin, stdout, ELK Stack, Elastic Stack Apache Kafka
アルゴリズム:Algorithms

Protected: Information Geometry of Positive Definite Matrices (2) From Gaussian Graphical Models to Convex Optimization

Information geometry of positive definite matrices utilized in digital transformation, artificial intelligence, and machine learning tasks From Gaussian graphical models to convex optimization (chordal graphs, triangulation graphs, dual coordinates, Pythagorean theorem, information geometry, geodesics, sample variance-covariance matrix, maximum likelihood Estimation, divergence, knot space, Riemannian metric, multivariate Gaussian distribution, Kullback-Leibler information measure, dual connection, Euclidean geometry, narrowly convex functions, free energy)
アルゴリズム:Algorithms

Protected: Measures for Stochastic Bandid Problems -Theoretical Limitations and the ε-Greedy Method

Theoretical limits and ε-greedy method, UCB method, riglet lower bounds for consistent measures, and KL divergence as measures for stochastic banded problems utilized in digital transformation , artificial intelligence , and machine learning tasks
微分積分:Calculus

Protected: Complexity of Hypothesis Sets in Statistical Mathematics Theory

Complexity of sets of hypotheses in statistical mathematical theory used in digital transformation, artificial intelligence, and machine learning tasks Rademacher complexity, VC dimension, large number factor, law of large uniform numbers, decision stocks, set of linear discriminators, set of linear functions, Cauchy-Schwartz inequality, Jensen inequality, Masar's complement, Talagrande's complement, empirical Rademacher complexity, Sauer's complement, Radon's theorem
アルゴリズム:Algorithms

Protected: Stochastic Optimization and Online Optimization Overview

Stochastic and online optimization used in digital transformation, artificial intelligence, and machine learning tasks expected error, riglet, minimax optimal, strongly convex loss function, stochastic gradient descent, stochastic dual averaging method, AdaGrad, online stochastic optimization, batch stochastic optimization
アルゴリズム:Algorithms

Protected: Unconstrained optimization for continuous optimization in machine learning

Unconstrained Optimization for Continuous Optimization in Machine Learning for Digital Transformation, Artificial Intelligence, and Machine Learning tasks machine epsilon, stopping conditions without scaling, stopping conditions with scaling, Taylor's theorem, stopping conditions for optimization algorithms, Hesse matrix
アルゴリズム:Algorithms

Protected: Unsupervised Learning with Gaussian Processes (1)Overview and Algorithm of Gaussian Process Latent Variable Models

Overview and algorithms of unsupervised learning using Gaussian Process Latent Variable Models GPLVM, an application of probabilistic generative models used in digital transformation, artificial intelligence, and machine learning, Bayesian Gaussian Process Latent Variable Models ,Bayesian GPLVM
アーキテクチャ

Installation and operation of Apache server and LAMP

Installation and operation of Apache server and LAMP (MariaDB, PHP, CentOS, Mac, Windows) utilized for digital transformation (DX), artificial intelligence (AI) and machine learning (ML) tasks
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