Projects sharing features with Machine Learning For Software Engineers

Readings for "A Unified View of Relational Deep Learning for Drug Pair Scoring." (IJCAI 2022)

A curated list of data mining papers about fraud detection.

A collection of research papers and software related to explainability in graph machine learning.

A list of popular deep learning models related to classification, segmentation and detection problems

A list of awesome and proven Artificial Intelligence use cases and applications

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 collection of research papers on decision, classification and regression trees with implementations.

A curated list of Monte Carlo tree search papers with implementations.

The definitive list of lists (of lists) curated on GitHub and elsewhere

This project is a comprehensive, community-curated directory that organizes a vast landscape of Python software libraries, frameworks, and tools. It serves as a centralized knowledge base designed to facilitate ecosystem navigation and accelerate developer discovery across the entire software development lifecycle. The directory distinguishes itself by providing a structured index of resources categorized by technical domain, ranging from foundational development utilities to specialized engineering fields. It covers high-level capabilities including artificial intelligence, data science, web

This project is a curated directory of resources, libraries, and frameworks designed to support the development, training, and deployment of neural network models. It serves as a comprehensive guide for navigating the machine learning ecosystem, providing structured access to software utilities and research materials. The directory distinguishes itself by aggregating tools across the entire machine learning lifecycle, ranging from data management and experiment tracking to production-ready model deployment. It functions as a central hub for discovering both foundational academic research and

This project is a community-maintained directory that serves as a comprehensive index of software tools, frameworks, and educational materials. It functions as an open-source knowledge base, organizing diverse engineering domains and technical resources into a structured taxonomy to assist developers in discovering high-quality content. The directory distinguishes itself through a decentralized peer-review model, where independent contributors curate, verify, and update entries to ensure accuracy and relevance. All information is stored in a version-controlled, flat-file markdown format, whic

A collection of important graph embedding, classification and representation learning papers with implementations.

A curated list of gradient boosting research papers with implementations.

A curated list of community detection research papers with implementations.

This project is a community-driven repository of high-quality, university-level computer science courses and learning materials. It serves as an open-source knowledge base, providing developers and students with direct access to structured curricula and academic resources designed to facilitate independent study and technical skill development. The repository distinguishes itself through a hierarchical taxonomy that organizes diverse technical subjects into a navigable structure. By utilizing markdown-based content curation, the project maintains a lightweight index of external links and refe

A curated list of awesome R packages, frameworks and software.

This repository serves as a comprehensive, curated collection of open-source implementations focused on artificial intelligence, machine learning, and computer vision. It functions as a centralized knowledge base and technical resource index, providing students and professional engineers with a structured directory of code examples for educational and practical reference. The project distinguishes itself through a community-driven curation model, relying on manual updates and contributions to maintain a relevant and expansive archive. By organizing these resources into categorized lists, the

Reinforcement learning resources curated

vscode-recipes is a collection of configuration patterns and guides for setting up debuggers and runtime environments within VS Code. It provides standardized templates and blueprints to connect the editor to local, containerized, or serverless runtimes across a variety of programming languages and frameworks. The project focuses on coordinating simultaneous debugging sessions across client-side and server-side processes to trace logic through full-stack applications. It offers specific patterns for integrating language runtimes and orchestrating multi-language development setups within a sin

:chartwithupwards_trend: A curated list of awesome data visualization libraries and resources.

:video_game: A curated list of awesome game datasets, and tools to artificial intelligence in games

This project is a comprehensive, crowdsourced directory of mathematical resources, functioning as a decentralized index of external educational materials. It organizes a vast collection of textbooks, lecture notes, and research tools into a hierarchical taxonomy, allowing users to navigate diverse mathematical disciplines through a version-controlled repository. The collection distinguishes itself by acting as a central hub for both academic discovery and practical application. It provides access to a wide array of interactive software, visualization tools, and step-by-step solvers designed t

This project is a curated repository of technical interview questions and a directory of study resources designed for professional software engineering assessments. It serves as a reference guide for interview patterns and common domain questions across various programming languages and technology stacks. The collection organizes coding and computer science questions by language and framework to assist with technical interview preparation and coding assessment study. It covers a wide range of programming domains and system design patterns to support software engineering career growth.

continuous integration and continuous delivery

Awesome OCR