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TypeScript Data Science
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- Snippet from Wikipedia: Data science
Data science is an interdisciplinary academic field that uses statistics, scientific computing, scientific methods, processing, scientific visualization, algorithms and systems to extract or extrapolate knowledge and insights from potentially noisy, structured, or unstructured data.
Data science also integrates domain knowledge from the underlying application domain (e.g., natural sciences, information technology, and medicine). Data science is multifaceted and can be described as a science, a research paradigm, a research method, a discipline, a workflow, and a profession.
Data science is "a concept to unify statistics, data analysis, informatics, and their related methods" to "understand and analyze actual phenomena" with data. It uses techniques and theories drawn from many fields within the context of mathematics, statistics, computer science, information science, and domain knowledge. However, data science is different from computer science and information science. Turing Award winner Jim Gray imagined data science as a "fourth paradigm" of science (empirical, theoretical, computational, and now data-driven) and asserted that "everything about science is changing because of the impact of information technology" and the data deluge.
A data scientist is a professional who creates programming code and combines it with statistical knowledge to create insights from data.
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TypeScript: TypeScript Glossary, TypeScript Best Practices, Web Development Best Practices, JavaScript Best Practices, TypeScript Fundamentals, TypeScript Inventor - TypeScript Language Designer: Anders Hejlsberg of Microsoft on October 1, 2012; TypeScript Keywords, TypeScript Built-In Data Types, TypeScript Data Structures - TypeScript Algorithms, TypeScript Syntax, TypeScript on Linux, TypeScript on macOS, TypeScript on Windows, TypeScript on Android, TypeScript on iOS, TypeScript Installation, TypeScript Containerization (TypeScript with Docker, TypeScript with Podman, TypeScript and Kubernetes), TypeScript OOP - TypeScript Design Patterns, Clean TypeScript - TypeScript Style Guide, TypeScript Best Practices - TypeScript BDD, Web Browser, Web Development, HTML-CSS, TypeScript Frameworks (Angular), JavaScript Libraries (React.js with TypeScript, Vue.js with TypeScript, jQuery with TypeScript), TypeScript on the Server (TypeScript with Node.js, TypeScript with Deno, TypeScript with Express.js), TypeScript Compiler (tsc, tsconfig.json), TypeScript Transpiler (Transpile TypeScript into JavaScript), Babel and TypeScript, TypeScript Package Management, NPM and TypeScript, NVM and TypeScript, Yarn Package Manager and TypeScript, TypeScript IDEs (Visual Studio Code, Visual Studio, JetBrains WebStorm), TypeScript Development Tools, TypeScript Linter, TypeScript Debugging (Chrome DevTools, JavaScript Source Maps), TypeScript Testing (TypeScript TDD, Selenium, Jest, Mocha.js, Jasmine, Tape Testing (tap-producing test harness for Node.js and browsers), Supertest, React Testing Library, Enzyme.js React Testing, Angular TestBed), TypeScript DevOps - TypeScript SRE, TypeScript Data Science - TypeScript DataOps, TypeScript Machine Learning, TypeScript Deep Learning, Functional TypeScript, TypeScript Concurrency (WebAssembly - WASM) - TypeScript Async (TypeScript Await, TypeScript Promises, TypeScript Workers - Web Workers, Service Workers, Browser Main Thread), TypeScript Concurrency, TypeScript History, TypeScript Bibliography, Manning TypeScript Series, TypeScript Glossary, TypeScript T, TypeScript Courses, TypeScript Standard Library, TypeScript Libraries, TypeScript Frameworks (Angular), TypeScript Research, JavaScript, TypeScript GitHub, Written in TypeScript, TypeScript Popularity, TypeScript Awesome, TypeScript Versions. (navbar_typescript - see also navbar_javascript, navbar_javascript_libraries, navbar_typescript_libraries, navbar_typescript_versions, navbar_typescript_standard_library, navbar_typescript_libraries, navbar_typescript_reserved_words, navbar_typescript_functional, navbar_typescript_concurrency, navbar_typescript_async, navbar_javascript_standard_library, navbar_react.js, navbar_angular, navbar_vue, navbar_javascript_standard_library, navbar_web_development)
Data Science: Fundamentals of Data Science, DataOps, Big Data, Data Science IDEs (Jupyter Notebook, JetBrains DataGrip, Google Colab, JetBrains DataSpell, SQL Server Management Studio, MySQL Workbench, Oracle SQL Developer, SQLiteStudio), Data Science Tools (SQL, Apache Arrow, Pandas, NumPy, Dask, Spark, Kafka); Data Science Programming Languages (Python Data Science, NumPy Data Science, R Data Science, Java Data Science, C++ Data Science, MATLAB Data Science, Scala Data Science, Julia Data Science, Excel Data Science (Excel is the most popular "programming language") - Google Sheets, SAS Data Science, C# Data Science, Golang Data Science, JavaScript Data Science, Kotlin Data Science, Ruby Data Science, Rust Data Science, Swift Data Science, TypeScript Data Science, Bash Data Science); Databases, Data, Augmentation, Analysis, Analytics, Archaeology, Cleansing, Collection, Compression, Corruption, Curation, Degradation, Editing (EmEditor), Data engineering, ETL/ ELT ( Extract- Transform- Load), Farming, Format management, Fusion, Integration, Integrity, Lake, Library, Loss, Management, Migration, Mining, Pre-processing, Preservation, Protection (privacy), Recovery, Reduction, Retention, Quality, Science, Scraping, Scrubbing, Security, Stewardship, Storage, Validation, Warehouse, Wrangling/munging. ML-DL - MLOps. Data science history, Data Science Bibliography, Manning Data Science Series, Data science Glossary, Data science topics, Data science courses, Data science libraries, Data science frameworks, Data science GitHub, Data Science Awesome list. (navbar_datascience - see also navbar_python, navbar_numpy, navbar_data_engineering and navbar_database)
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