Repository History
8 repositories tagged with Data Science
fastFM: A High-Performance Python Library for Factorization Machines
fastFM is a powerful Python library designed for Factorization Machines, offering high-performance implementations of various optimization routines. It integrates seamlessly with the scikit-learn API, making it accessible for machine learning practitioners. The library supports regression, classification, and ranking problems, leveraging C and Cython for speed-critical operations.
Rio: Build Web and Desktop Apps in Pure Python, No JavaScript Needed
Rio is an innovative Python framework that allows developers to create web and desktop applications using pure Python, eliminating the need for HTML, CSS, or JavaScript. It provides a modern, declarative UI approach with over 50 built-in components, making app development efficient and enjoyable. With Rio, you can build powerful, type-safe applications that run seamlessly across different environments.
TabSTAR: A Tabular Foundation Model for Data with Text Fields
TabSTAR is an innovative tabular foundation model designed to effectively process tabular data that includes text fields. It offers a user-friendly package for integrating pretrained models into your own datasets, alongside a comprehensive research mode for advanced development and benchmarking. This powerful tool simplifies the application of deep learning to complex tabular structures.
nolds: Nonlinear Measures for Dynamical Systems in Python
nolds is a Python library for calculating nonlinear measures in dynamical systems, specifically designed for one-dimensional time series. It provides implementations for various metrics such as sample entropy, correlation dimension, Lyapunov exponents, and Hurst exponent. This tool is valuable for analyzing the complexity, predictability, and memory of time series data, serving as both a practical utility and a learning resource.
DataScienceInteractivePython: Interactive Dashboards for Learning Data Science
DataScienceInteractivePython is a GitHub repository by Professor Michael Pyrcz, offering interactive Python dashboards designed to simplify the learning process for data science concepts. It provides hands-on tools for students and enthusiasts to explore statistics, models, and theoretical concepts through engaging, interactive examples. This resource aims to remove barriers to education by allowing users to experiment with data analytics and machine learning in real-time.
Lance: Modern Columnar Data Format for ML and LLMs
Lance is a modern columnar data format, implemented in Rust, designed for machine learning and large language model workflows. It offers significant performance improvements over Parquet for random access, includes vector indexing, and supports data versioning. Compatible with popular tools like Pandas, DuckDB, and PyTorch, Lance streamlines data management for ML applications.
Gradio: Build and Share Machine Learning Apps in Python
Gradio is an open-source Python library that simplifies the creation and sharing of interactive web applications for machine learning models, APIs, or any Python function. It allows developers to quickly build user interfaces without needing JavaScript, CSS, or web hosting expertise, offering a straightforward way to demo AI projects. With Gradio, you can transform your Python functions into shareable web demos in just a few lines of code.
Numba: A Just-In-Time Compiler for Numerical Python Functions
Numba is an open-source, NumPy-aware optimizing compiler for Python, leveraging the LLVM project to generate machine code. It significantly accelerates numerical functions, offering support for automatic parallelization, GPU-accelerated code, and ufuncs. This tool is essential for Python developers seeking high-performance computing capabilities.