ICT技術:ICT Technology About Machine Learning Technology
Machine learning techniques used for digital transformation (DX) and artificial intelligence (AI) tasks
ICT技術:ICT Technology
ICT技術:ICT Technology プログラミング言語:Programming Language Data types and statically and dynamically typed languages in programming
Types of data and statically typed languages and dynamically typed languages (primitive types, heap, Ruby, Python, C#, C++, Java, classes, objects, alias problems, garbage collection, Rust, Borrow checkers, stacks, global variables, value types, reference types, complex types, enumeration types) in programming used for digital transformation, artificial intelligence, machine learning.
python Protected: Applying Neural Networks to Reinforcement Learning Deep Q-Network Applying Deep Learning to Value Assessment
Application of Neural Networks to Reinforcement Learning for Digital Transformation, Artificial Intelligence, and Machine Learning tasks Deep Q-Network Prioritized Replay, Multi-step applying deep learning to value assessment Deep Q-Network applying deep learning to value assessment (Prioritized Replay, Multi-step Learning, Distibutional RL, Noisy Nets, Double DQN, Dueling Network, Rainbow, GPU, Epsilon-Greedy method, Optimizer, Reward Clipping, Fixed Target Q-Network, Experience Replay, Average Experience Replay, Mean Square Error, Mean Squared Error, TD Error, PyGame Learning Enviroment, PLE, OpenAI Gym, CNN
Clojure Protected: Network analysis in GraphX Pregel using Clojure
Network analysis in GraphX Pregel using Clojure for digital transformation, artificial intelligence, and machine learning tasks (label propagation, twitter data, community analysis, graph structure analysis, community size, community detection, algorithms, maximum connected components, triangle counting, glittering, Google, Koenigsberg bridge, Euler path)
アーキテクチャ AWS Cloud Service Design Patterns (2)
AWS Cloud Service Design Patterns used for Digital Transformation, Artificial Intelligence and Machine Learning tasks (Data Upload Patterns, Write Proxy, Storage Index, Direct Object Upload, Relational Database Patterns, DB Replication, Read Replica, Inmemory DB Cache, Sharing Write, Asynchronous Processing, Batch Processing Patterns, Queuing Chain, Priority Queue, Job Observer, Fanout)
web技術:web technology ISWC2022Papers
ISWC2022Papers
From ISWC2022, an international conference on Semantic Web technologies, one of the artificial ...
コンピューター Various approaches to realize optical computers
Various approaches to realize optical computers to exploit digital transformation, artificial intelligence, and machine learning tasks (fractals, ultra-high definition spatial light modulators, stereoscopic images, self-reproducing software, self-reproducing hardware, Spatial Light Modulator, SLM, Spatial Modulator, Colloidal diamond, Plastic, Photonic crystal, Diamond, 5D data storage, Nanostructure, Superman Memory Crystal, Superman, Fortress of Solitude)
Clojure Protected: Network Analysis Using Clojure (2)Computing Triangles in a Graph Using Glittering
Network analysis using triangle computation in graphs using Clojure/Glittering for digital transformation, artificial intelligence, and machine learning tasks (GraphX, Pregel API, Twitter dataset, custom triangle count algorithm, message send function, message merge function, outer join, RDD, vertex attributes, Apache Spark, Sparkling, MLlib, Glittering, triangle counting, edge-cut strategy, random-vertex-cut strategy, and social networks, graph parallel computing functions, Hadoop, data parallel systems, RDG, Resilient Distributed Graph, Hama, Giraph)
web技術:web technology Protected: Setup of Terraform, an infrastructure management tool
Setup of Terraform, an infrastructure management tool used for digital transformation, artificial intelligence, and machine learning tasks (git-secrets, dockernized Terraform, AWS credentials, team development tfenv, Homebrew, AWS CLI, AWS Management Console, access key ID, secret access key, python, Identity and Access Management, AWS, environment setup)
アーキテクチャ AWS Cloud Service Design Patterns (1)
AWS Cloud Service Design Patterns for Digital Transformation, Artificial Intelligence, and Machine Learning tasks (Snapshot, Stamp, Scale Up, Scale Out, Ondemand Disk, Multi-Server, Multi-Datacenter, Floating IP, Deep Health Check, Routing-Based HA, Clone Server, NFS Sharing, NFS Replica, State Sharing, URL Rewriting, Rewrite Proxy, and Datacenter). Datacenter, Floating IP, Deep Health Check, Routing-Based HA, Clone Server, NFS Sharing, NFS Replica, State Sharing, URL Rewriting, Rewrite Proxy, Cache Proxy, Scheduled Scale Cache Proxy, Scheduled Scale Out, IP Pooling, Web Storage, Direct Hosting, Private Distribution, Cache Distribution, Rename Distribution, Private Cache Distribution, Latency Based Origin)