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Swift Data Science
Return to iOS Development and Data Science, Data Science, Machine Learning - Deep Learning, Swift Machine Learning, DataOps-MLOps-DevOps, Swift Official Glossary, Swift Topics, Swift, Swift DevOps - Swift SRE, Swift DataOps, Swift MLOps
- 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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Swift: Swift Fundamentals, Swift Inventor - Swift Language Designer: Chris Lattner, Doug Gregor, John McCall, Ted Kremenek, Joe Groff of Apple Inc. on June 2, 2014; SwiftUI, Apple Development Kits - Apple SDKs (CloudKit, CoreML-ARKit - SiriKit - HomeKit, Foundation Kit - UIKit - AppKit, SpriteKit), Swift Keywords, Swift Built-In Data Types, Swift Data Structures (Swift NSString String Library, Swift NSArray, Swift NSDictionary, Swift Collection Classes) - Swift Algorithms, Swift Syntax, Swift Access Control, Swift Option Types (Swift Optionals and Swift Optional Chaining), Swift Protocol-Oriented Programming, Swift Value Types, Swift ARC (Swift Automatic Reference Counting), Swift OOP - Swift Design Patterns, Clean Swift - Human Interface Guidelines, Swift Best Practices - Swift BDD, Swift Apple Pay, Swift on iOS - Swift on iPadOS - Swift on WatchOS - Swift on AppleTV - Swift on tvOS, Swift on macOS, Swift on Windows, Swift on Linux, Swift installation, Swift Combine framework (SwiftUI framework - SwiftUI, UIKit framework - UIKit, AppKit framework - AppKit, Cocoa framework - Cocoa API (Foundation Kit framework, Application Kit framework, and Core Data framework (Core Data object graph and Core Data persistence framework, Core Data object-relational mapping, Core Data ORM, Core Data SQLite), Apple Combine asynchronous events, Apple Combine event-processing operators, Apple Combine Publisher protocol, Apple Combine Subscriber protocol), Swift containerization, Swift configuration, Swift compiler, Swift IDEs (Apple Xcode (Interface Builder, nib files), JetBrains AppCode), Swift development tools (CocoaPods dependency manager, Swift Package Manager, Swift debugging), Swift DevOps (Swift scripting, Swift command line, Swift observability, Swift logging, Swift monitoring, Swift deployment) - Swift SRE, Swift data science (Core Data, Realm-RealmSwift, Swift SQLite, Swift MongoDB, Swift PostgreSQL), Swift machine learning (Core ML), Swift AR (ARKit), SiriKit, Swift deep learning, Swift IoT (HomeKit), Functional Swift (Swift closures (lambdas - effectively “Swift lambdas”), Swift anonymous functions), Swift concurrency (Apple Combine framework, Swift actors, Swift async, Swift async/await, Grand Central Dispatch (GCD or libdispatch), Swift on multi-core processors, Swift on symmetric multiprocessing systems, Swift task parallelism, Swift thread pool pattern, Swift parallelism), Reactive Swift (RXSwift), Swift testing (XCTest framework, Swift TDD, Swift mocking), Swift security (Swift Keychain, Swift secrets management, Swift OAuth, Swift encryption), Swift server-side - Swift web (Swift Vapor, Swift Kitura), Swift history, Swift bibliography, Manning Swift Series, Swift glossary, Swift topics, Swift courses, Swift Standard Library (Swift REST, Swift JSON, Swift GraphQL), Swift libraries, Swift frameworks (Apple Combine framework, SwiftUI), Swift research, WWDC, Apple GitHub - Swift GitHub, Written in Swift, Swift popularity, Swift Awesome list, Swift Versions, Objective-C. (navbar_swift - see also navbar_iphone, navbar_ios, navbar_ipad, navbar_mobile)
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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