Protected: Regression analysis using Clojure (2) Multiple regression model
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Overview of web crawling technologies and implementation in Python/Clojure
Overview of web crawling technologies used for digital transformation, artificial intelligence and machine learning tasks and their implementation in Python/Clojure jsoup, clj-http, enlive, clojure.data.json, HTML, CSS jsoup, HTML, CSS, XPATH, JSON, BeautifulSoup, Scrapy, data extraction, natural language processing, databases, search, SNS analysis
Overview of Kubernetes, environment setup, and reference books
Overview and configuration of Kubernetes used for digital transformation, artificial intelligence and machine learning tasks, reference books (Microservices, Spinnaker, Blue, Containers, Cloud Natives, Skaffold, Clair, Security, BuildKit, Kaniko, Operator, Helm, Chart, Sock Shop, YAML, Prometheus, Grafana, Pod, Minikube)
On the Road to Inaba and Hoki
Ryotaro Shiba's Road to Inaba and Hoki (Eshima Ohashi Bridge, Beta Tread Bridge, Mizuki Shigeru Road, Mizuki Shigeru Memorial Museum, Sakaiminato, Kaike Onsen, Kaike Triathlon, Hoki Daisen, Kurayoshi, Kurayoshi Kasuri, Ikinoshima, Inaba no Shirousagi, Okuninushi no Mikoto, Yatsujin, Izumo Country, Inaba no Genza, Myokojin, Yanagi Muneyoshi, D. T. Suzuki, Zen, folk art, Japan Folk Mingeikan, Manyoshu, Otomo Iemochi, Taika no Kaihin, Soga Iruka, Prince Nakataio, Inaba no Kokubu, Hayano, Nagisan, Momotaro, Izumo Taisha, Yaqi Taibe, Susano-onomikoto, Kibitsuhiko-nomikoto, Chizu-cho, Tottori, Chugoku Mountains)
Protected: What is Philosophy from the Special Lecture “Socrates’ Defense”
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Protected: Optimal arm bandit and Bayes optimal when the player’s candidate actions are large or continuous(1)
Optimal arm bandit and Bayes optimal linear curl, linear bandit, covariance function, Mattern kernel, Gaussian kernel, positive definite kernel function, block matrix, inverse matrix formulation, prior simultaneous probability density, Gaussian process, Lipschitz continuous, Euclidean norm, simple riglet, black box optimization, optimal arm identification, regret, cross checking, leave-one-out cross checking, continuous arm bandit
Protected: Sparse machine learning based on trace-norm regularization
Sparse machine learning based on trace norm regularization for digital transformation, artificial intelligence, and machine learning tasks PROPACK, random projection, singularity decomposition, low rank, sparse matrix, update formula for proximity gradient, collaborative filtering, singular value solver,. Trace norm, prox action, regularization parameter, singular value, singular vector, accelerated proximity gradient method, learning problem with trace norm regularization, semidefinite matrix, square root of matrix, Frobenius norm, Frobenius norm squared regularization, Torres norm minimization, binary classification problem, multi-task learning group L1 norm, recommendation systems
Protected: Optimality conditions for constrained inequality optimization problems in machine learning
Optimality conditions for constrained inequality optimization problems in machine learning used in digital transformation, artificial intelligence, and machine learningtasks duality problems, strong duality, Lagrangian functions, linear programming problems, Slater conditions, principal dual interior point method, weak duality, first order sufficient conditions for convex optimization, second order sufficient conditions, KKT conditions, stopping conditions, first order optimality conditions, valid constraint expressions, Karush-Kuhn-Tucker, local optimal solutions
Protected: Fundamentals of convex analysis in stochastic optimization (1) Convex functions and subdifferentials, dual functions
Convex functions and subdifferentials, dual functions (convex functions, conjugate functions, Young-Fenchel inequality, subdifferentials, Lejandre transform, subgradient, L1 norm, relative interior points, affine envelope, affine set, closed envelope, epigraph, convex envelope, smooth convex functions, narrowly convex functions, truly convex closed functions, closed convex closed functions, execution domain, convex set) in basic matters of convex analysis in stochastic optimization used for Digital Transformation, Artificial Intelligence, Machine Learning tasks.
Protected: Image feature extraction and missing value inference in linear dimensionality reduction models in Bayesian inference
Image feature extraction and missing value inference (missing image information recovery, defect value interpolation, variational inference, unfilled questionnaires, unfilled profile information, multiple sensor integration, linear dimensionality compression algorithm, image lossy compression) in linear dimensionality reduction model in Bayesian inference used for digital transformation, artificial intelligence, machine learning tasks.