Features
Everything on SkillVeris tagged Features — collected across the glossary, study notes, blog, and cheat sheets.
13 resources across 1 library
Study Notes(13)
Server Roles and Features
Understand the distinction between Windows Server roles and features, and how to add them using Server Manager and PowerShell.
Accessing Device Features
Explore the Microsoft.Maui.Essentials device APIs for geolocation, camera, sensors, and connectivity in .NET MAUI.
Features of C++
Explore the core features of C++ — from object-oriented programming to portability and performance — that make it a powerful systems language.
Features of C
Explore the core features of C — portability, speed, modularity, pointers, and rich operators — that make it a systems programming staple.
Features of Java
Explore the core features that make Java popular — object-oriented design, platform independence, robustness, security, multithreading, and high performance vi…
Features of Python
A tour of Python's core language features — dynamic typing, simplicity, portability, extensive libraries, and more — that explain its widespread adoption.
Features of JavaScript
A survey of JavaScript's core characteristics: dynamic typing, first-class functions, prototypal inheritance, and asynchronous support.
Features of TypeScript
A tour of TypeScript's core language features — static typing, interfaces, generics, and tooling — that set it apart from plain JavaScript.
Features of Go
An overview of Go's core language features, including concurrency, garbage collection, and simple syntax.
Features of Rust
An overview of the core language features that make Rust safe, fast, and productive to use.
Features of Kotlin
An overview of Kotlin's core language features, including null safety, concise syntax, and multi-paradigm support.
Features of Swift
Swift combines safety, speed, and modern syntax through optionals, type inference, ARC, and a powerful LLVM-based compiler.
Datasets, Features, and Labels
Explains the vocabulary and structure of ML data — datasets, samples, features, and labels — and how they are organized before a model can be trained.