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🧙 Build, run, and manage data pipelines for integrating and transforming data.
Fit interpretable models. Explain blackbox machine learning.
typing puzzles for youtube.com/anthonywritescode
A lightning-fast Zig-powered event loop for Python's asyncio.
mRMR (minimum-Redundancy-Maximum-Relevance) for automatic feature selection at scale.
LinearBoost Classifier is a rapid and accurate classification algorithm that builds upon a very fast, linear classifier.
A high performance caching library for Python written in Rust
Practical mutation testing and fault injection for C and C++
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
The book every data scientist needs on their desk.
MicroRabbit: A lightweight, asynchronous Python framework for RabbitMQ that simplifies building microservices and distributed systems. Features include easy message routing, plugin support, and int…
Shapley Interactions and Shapley Values for Machine Learning
A modern cookiecutter template for Python projects that use uv for dependency management
Multi Model Server is a tool for serving neural net models for inference
A high-performance ML model serving framework, offers dynamic batching and CPU/GPU pipelines to fully exploit your compute machine
The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!
Standardized Serverless ML Inference Platform on Kubernetes
A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques
Simple, powerful, and fast logging for Python.
MinIO is a high-performance, S3 compatible object store, open sourced under GNU AGPLv3 license.
The fastest way to create an HTML app
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
nannyml: post-deployment data science in python