Repository History
9 repositories tagged with data-science
awesome-R: A Curated List of Essential R Packages and Tools
awesome-R is a highly popular GitHub repository, maintained by qinwf, offering a meticulously curated list of R packages, frameworks, and software. It serves as an invaluable resource for anyone working with R, from data analysis to machine learning. With over 6,400 stars, it stands as a testament to its utility and community recognition.
Evidently: Open-Source ML and LLM Observability Framework
Evidently is an open-source Python library designed for evaluating, testing, and monitoring machine learning and large language model systems. It provides over 100 built-in metrics for various tasks, from data drift detection to LLM judges, supporting both tabular and text data. This framework helps ensure the quality and performance of AI-powered systems throughout their lifecycle.
TensorRec: A TensorFlow Recommendation Framework in Python
TensorRec is a Python recommendation system built on TensorFlow, designed for quickly developing and customizing recommendation algorithms. It allows users to define custom representation and loss functions while handling data manipulation, scoring, and ranking. Although not under active development, it provides a solid foundation for understanding and implementing recommender systems.
ML-From-Scratch: Machine Learning Models and Algorithms in NumPy
ML-From-Scratch is a comprehensive GitHub repository offering bare-bones NumPy implementations of fundamental machine learning models and algorithms. It emphasizes accessibility, making complex concepts easier to understand for learners and practitioners. This project covers a wide range of topics, from linear regression to deep learning and reinforcement learning, all implemented from scratch.
Spotlight: Deep Recommender Models with PyTorch
Spotlight is a Python library built on PyTorch for developing deep and shallow recommender models. It offers a comprehensive set of building blocks for various loss functions, representations, and utilities for handling recommendation datasets. This tool is designed for rapid exploration and prototyping of new recommender systems.
Conda: A Cross-Platform Binary Package and Environment Manager
Conda is a powerful, cross-platform, language-agnostic binary package and environment manager. It simplifies the creation of isolated environments for various projects, even for C libraries, and efficiently installs packages using hard links. Written entirely in Python and BSD licensed, Conda is a cornerstone for distributions like Anaconda and Miniforge.
RecDebiasing: A Comprehensive Collection of Recommendation Debiasing Methods
RecDebiasing is a valuable GitHub repository that curates a wide array of debiasing methods for recommendation systems. It compiles recent research papers, relevant datasets, and associated codebases, offering a centralized resource for understanding and addressing various biases. This collection is essential for researchers and practitioners focused on building more fair and accurate recommender systems.
scikit-learn: The Essential Python Library for Machine Learning
scikit-learn is a widely-used open-source Python library for machine learning, built upon SciPy. It provides a comprehensive suite of tools for data mining and data analysis, making it an indispensable resource for developers and data scientists. With its extensive algorithms and user-friendly interface, scikit-learn simplifies complex machine learning tasks.
OpenLLMetry: Open-Source Observability for LLM Applications with OpenTelemetry
OpenLLMetry provides open-source observability for Generative AI (GenAI) and Large Language Model (LLM) applications, built upon the OpenTelemetry standard. It offers comprehensive tracing and monitoring capabilities, allowing seamless integration with existing observability solutions like Datadog, Honeycomb, and Grafana. This project simplifies the process of gaining insights into your LLM-powered systems.