overview

コンピューター

Overview of Semiconductor Manufacturing Technology and Application of AI Technology

Overview of semiconductor manufacturing technology and application of AI technology front-end process, wafer fabrication, cleaning process, deposition process, lithography process, etching process, impurity diffusion process, etc.; back-end process, dicing, mounting, bonding, molding, marking, bumping process, packaging, diffusion, ion implantation Annealing, wet etching, dry etching, immersion lithography system, EUV, AR excimer laser, Moore's law, 2nm, photosensitizer, photoengraving technology, stepper, thermal oxidation, CVD, sputter, Choklarsky method, ingot, Si wafer
Symbolic Logic

Overview of the Knowledge Graph and summary of related presentations at the International Society for the Study of Knowledge Graphs (ISWC)

Overview of knowledge graphs used for digital transformation, artificial intelligence, and machine learning tasks and summary of related presentations at the International Society for the World Wide Web Conference ISWC (ISWC, natural language processing, reasoning techniques, data analytics, robotics, IOT, search engine, inference engine Entity Extraction, Picture Entity Linking, Relational Learning, Deep Learning, Fusion of Logic and Probability, Relationship Extraction, Topic Models, Chatbots, Question Answering, Semantic Web Technologies, Knowledge Information Processing, RDF Store, SPARQL, Ontology Matching, Database Technologies)
web技術:web technology

Overview of Container Technology and Docker for Cloud Native

Overview of container technologies that enable cloud-native utilized for digital transformation, artificial intelligence, and machine learning tasks and Docker container images, build/push functionality, cri-o, container execution, Kubernetes, the containerd, CRI-Containerd, low-level container runtime, high-level container runtime, kernel functionality, Open Container Initiative, OCI, Runtime Specification, Format Specification, Copy-on-Write, COW, cgroups, hierarchies, file systems, namespaces, virtual OS, Paas, Linux
アルゴリズム:Algorithms

Protected: Overview of nu-Support Vector Machines by Statistical Mathematics Theory

Overview of nu-support vector machines by statistical mathematics theory utilized in digital transformation, artificial intelligence, and machine learning tasks (kernel functions, boundedness, empirical margin discriminant error, models without bias terms, reproducing nuclear Hilbert spaces, prediction discriminant error, uniform bounds Statistical Consistency, C-Support Vector Machines, Correspondence, Statistical Model Degrees of Freedom, Dual Problem, Gradient Descent, Minimum Distance Problem, Discriminant Bounds, Geometric Interpretation, Binary Discriminant, Experience Margin Discriminant Error, Experience Discriminant Error, Regularization Parameter, Minimax Theorem, Gram Matrix, Lagrangian Function).
ICT技術:ICT Technology

What is Docker? Advantages and Challenges, Differences from Virtualization Infrastructure and Architecture Overview

Advantages and challenges of Docker used for digital transformation, artificial intelligence, and machine learning tasks, differences from virtualization infrastructure and architecture overview cgroups, resource management tools, virtual files, Linux kernel, Windows, Windows Server, pid namespace, user namespace, uts namespace, net namespace, nmt namespace, ipc namespace, hypervisor type, namespace, virtualization software, WIndows Server Container, non-stop server, mission-critical Live Migration, Capacity Planning, Orchestration, kubernetes, Immutable Infrastructure, Disposable Components, Loosely Coupled, IaaS, Cloud Computing
python

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)
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: 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
アルゴリズム:Algorithms

Protected: Supervised learning and regularization

Overview of supervised learning regression, discriminant and regularization ridge function, L1 regularization, bridge regularization, elastic net regularization, SCAD, group regularization, generalized concatenated regularization, trace norm regularization as the basis of machine learning optimization methods used for digital transformation, artificial intelligence and machine learning tasks
アーキテクチャ

Protected: Transition from monolithic services to microservices and service design

Overview of migration from monolithic services and design guidelines for microservices leveraged for digital transformation, artificial intelligence, and machine learning tasks (release cycle and deployment process, boundary context, productivity, components, service-oriented architecture, database isolation)
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