A curated list of all machine learning algorithms and deep learning algorithms grouped by category.
Les fonctionnalités principales de sahith02/machine-learning-algorithms sont : Awesome List, Educational Resources, Curated Lists.
Les alternatives open-source à sahith02/machine-learning-algorithms incluent : awesomedata/awesome-public-datasets — This project is a community-maintained, open-access directory of high-quality public datasets. It serves as a… ossu/computer-science — This project provides a structured computer science curriculum framework designed for self-directed learners. It… codecrafters-io/build-your-own-x — This project provides a comprehensive framework for creating, managing, and executing educational programming… sindresorhus/awesome — This project is a community-maintained directory that serves as a comprehensive index of software tools, frameworks,… onurakpolat/awesome-bigdata — A curated list of awesome big data frameworks, ressources and other awesomeness. 0xnr/awesome-analytics — This project is a curated directory of analytics frameworks and software designed to help users discover tools for…
This project is a community-maintained, open-access directory of high-quality public datasets. It serves as a centralized reference point for researchers, developers, and data scientists to locate reliable information sources across a wide spectrum of industries and scientific fields. By providing a structured index, the repository facilitates the discovery of data necessary for exploratory analysis, machine learning model training, and the development of data-intensive applications. The directory distinguishes itself through a lightweight, platform-agnostic approach to resource indexing that
This project provides a comprehensive framework for creating, managing, and executing educational programming challenges. It includes standardized systems for authoring instructional content, defining test cases, and structuring documentation to ensure consistent learning outcomes. The platform supports a wide range of programming languages through dedicated execution environments that handle compilation, dependency management, and automated testing. The infrastructure facilitates both local and remote development workflows, offering command-line utilities for testing code without requiring v
A curated list of awesome big data frameworks, ressources and other awesomeness.
This project provides a structured computer science curriculum framework designed for self-directed learners. It organizes open-access academic resources, including textbooks, lectures, and assignments, into a cohesive path that mirrors the requirements of a formal undergraduate degree. By integrating theoretical study with practical software engineering methodologies, the platform enables students to master foundational concepts and advanced technical skills independently. The curriculum distinguishes itself by utilizing a version-control-based workflow to manage the educational experience.