December 2022 | Page 2 | Deus Ex Machina

Protected: On-line Stochastic Optimization and Stochastic Dual Averaging (SDA) for Machine Learning

On-line stochastic optimization and stochastic dual averaging methods for machine learning (mirror image descent, strongly convex functions, convex functions, convergence rates, polynomial decay averaging, strongly convex regularization) for digital transformation, artificial intelligence and machine learning tasks.

2022.12.21

Uncategorized

Protected: Basics of gradient method (linear search method, coordinate descent method, steepest descent method and error back propagation method)

Fundamentals of gradient methods utilized in digital transformation, artificial intelligence, and machine learning tasks (linear search, coordinate descent, steepest descent and error back propagation, stochastic optimization, multilayer perceptron, adaboost, boosting, Wolf condition, Zotendijk condition, Armijo condition, backtracking methods, Goldstein condition, strong Wolf condition)

2022.12.20

アルゴリズム:Algorithms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: Machine Learning with Bayesian Inference – Mixture Models, Data Generation Process and Posterior Distribution

Mixture models and data generation processes and posterior distributions (graphical models, Poisson distribution, Gaussian distribution, Dirichlet distribution, categorical distribution) in machine learning with Bayesian inference used in digital transformation, artificial intelligence, machine learning

2022.12.19

アルゴリズム:Algorithmsグラフ理論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

On the Road to Shirakawa and Aizu

Ryotaro Shiba's Road to Shirakawa and Aizu Masayuki Hoshina, Aizu Culture, Ujisato Gamo, Aizu Wakamatsu, Boshin War, Ou-Koshi Alliance, Yoshinobu Tokugawa, Rin Yamashita, Russian Orthodox Church, Iconostas, Holy Image Painting, Shirakawa Christian Orthodox Church Cathedral, Nikolai Cathedral, Resurrection Cathedral, Eihei Hanshokusui, Soto sect, Dogen, Sekikawa Temple, Kim. Yachimizo, Sakai no Myojin, Tamatsushima Myojin, Sumiyoshi Myojin, Matsudaira Sadanobu, Shirakawa Seki, Old Sekiseki, New Shirakawa Station, Tohoku Shinkansen, Genyu, Matsuo Basho, Oku no Hosomichi, Kokin Wakashu, Natori River, trifoliate garden, Nobuo Mojizuri

2022.12.18

旅歴史紀行読書

Protected: Explainable Artificial Intelligence (9) Model-independent interpretation (ALE plot)

ALE plot is one of the posterior interpretation models that can be explained and used for digital transformation (DX), artificial intelligence (AI), and machine learning (ML).

2022.12.16

推論技術:inference Technology検索技術:Search Technology機械学習:Machine Learning

Protected: Large-scale Machine Learning with Apache Spark and MLlib

Large-scale machine learning with Apache Spark and MLlib for digital transformation, artificial intelligence, and machine learning tasks (predictive value, RMSE, factor matrix, rank, latent features, neighborhoods, sum of squares error, Mahout, ALS, Scala RDD, alternating least squares, alternating least squares, stochastic gradient descent, persistence, caching, Flambo, Clojure, Java)

2022.12.15

ClojureLarge-Scaleデータアルゴリズム:Algorithms機械学習:Machine Learning

Protected: the application of neural networks to reinforcement learning(1) overview

Overview of the application of neural networks to reinforcement learning utilized in digital transformation, artificial intelligence and machine learning tasks (Agent, Epsilon-Greedy method, Trainer, Observer, Logger, Stochastic Gradient Descent, Stochastic Gradient Descent, SGD, Adaptive Moment Estimation, Adam, Optimizer, Error Back Propagation Method, Backpropagation, Gradient, Activation Function Stochastic Gradient Descent, SGD, Adaptive Moment Estimation, Adam, Optimizer, Error Back Propagation, Backpropagation, Gradient, Activation Function, Batch Method, Value Function, Strategy)

2022.12.14

pythonアルゴリズム:Algorithms強化学習微分積分:Calculus最適化:Optimization機械学習:Machine Learning深層学習:Deep Learning確率・統計:Probability and Statistics

Introduction and configuration of Apache Spark for distributed data processing

Deployment and configuration of Apache Spark to enable distributed data processing for digital transformation, artificial intelligence and machine learning tasks (NodeManager, YARN, spark-master, ResourceManager, spark-worker, HDFS, NameNode, DataNode, spark-client, CDH5.4, haddop, Yum, CentOS) spark-worker, HDFS, NameNode, DataNode, spark-client, CDH5.4, haddop, Yum, CentOS)

2022.12.13

IOT技術:IOT TechnologyStream Data Processingweb技術:web technologyアーキテクチャコンピューター時系列データ解析

Deploying and Operating Microservices – Docker and Kubernetes

Deployment and operation of microservices leveraged for digital transformation, artificial intelligence and machine learning tasks - Docker and Kubernetes minikube, containers, deployment, kube-ctl, rolling-upgrade, auto-bin packing, horizontal scaling, scale-up, scale-down, self-healing, kubelet, kube-apiserver, etcd, kube-controller- manager, kube- scheduler, pod, kube-proxy, Docker CLI, the Docker Registry, cgroups, Linux kernel, kernel namespace, union mount option, Hypervisor

2022.12.12

アーキテクチャコンピューターネットワーク技術マルチエージェントシステム

Machine Learning by Ensemble Methods – Fundamentals and Algorithms Reading Notes

Fundamentals and algorithms in machine learning with ensemble methods used in digital transformation, artificial intelligence and machine learning tasks class unbalanced learning, cost-aware learning, active learning, semi-supervised learning, similarity-based methods, clustering ensemble methods, graph-based methods, festival label-based methods, transformation-based methods, clustering, optimization-based pruning, ensemble pruning, join methods, bagging, boosting

2022.12.11

アルゴリズム:Algorithms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

2022-12