Open-source alternatives to Awesome Datascience

This project is a curated knowledge repository that serves as a comprehensive directory for computer science education, focusing on algorithms and data structures. It provides a structured index of resources designed to assist developers in mastering computational problem-solving techniques, ranging from fundamental theory to advanced applications. The directory distinguishes itself by aggregating diverse learning materials, including interactive visualization tools, competitive programming platforms, and technical interview preparation guides. By organizing these resources into a hierarchica

This project is a community-driven directory that aggregates and categorizes high-quality technical resources, tools, and learning materials. It functions as a centralized knowledge management repository, designed to help developers navigate the software development landscape by providing structured access to curated lists and external project references. The directory relies on a collaborative, peer-reviewed workflow where external contributors submit and maintain links through a version-controlled system. This community-maintained approach ensures that the information remains current and re

A curated list of awesome information retrieval resources

A curated list of speech and natural language processing resources

🔬 A curated list of awesome LLMs & deep learning strategies & tools in financial market.

A curated list of deep learning resources for computer vision

Awesome Explainable AI (XAI) and Interpretable ML Papers and Resources

Awesome TensorFlow.js - A curated list of dedicated resources to master TensorFlow.js

Curated list of Linguistic Resources for doing NLP & CL on Spanish

A curated list of delightful Conversational AI resources.

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

A curated list of software, tools, pipelines, plugins etc. for image analysis related to biological questions.

A curated list of notable ETL (extract, transform, load) frameworks, libraries and software.

This project is a comprehensive cybersecurity knowledge repository that provides a structured collection of technical documentation, training materials, and professional development roadmaps. It serves as a centralized resource for practitioners to navigate complex security disciplines, ranging from offensive and defensive fundamentals to specialized infrastructure and application security. The repository distinguishes itself through a modular resource framework that enables users to construct isolated cyber range environments for hands-on practice. It also features a specialized reference gu

A curated list of community detection research papers with implementations.

:book: A curated list of resources dedicated to Natural Language Processing (NLP)

This project is a comprehensive, community-curated directory of resources and methodologies for open-source intelligence gathering. It serves as a centralized reference framework for researchers, providing a structured index of specialized tools, databases, and search techniques used to collect and analyze publicly available information from across the global internet. The directory distinguishes itself through a hierarchical taxonomy that organizes complex investigative domains, ranging from cyber threat intelligence and digital forensic investigation to geospatial analysis and operational s

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.

Awesome online talks and screencasts

Note from the Editor: Take Two

Curated list: Resources for machine learning in Ruby

A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai)

A curated list of awesome quantum computing learning and developing resources.

Awesome-Pytorch-list