Showing 81-100 of 438 projects
This is a Python library for machine learning that appears to be a part of the Apple ecosystem.
Provides explanations of key concepts in machine learning for developers.
BentoML is an easy-to-use framework for building and deploying production-ready machine learning models as APIs.
A high-performance Python library for working with large tabular datasets, offering efficient data manipulation and visualization.
A WebGL-accelerated JavaScript library for machine learning and deep learning on the web.
Caffe2 is a lightweight, scalable deep learning framework for building and deploying AI models.
A collection of examples demonstrating the usage of the MLX framework for building AI-powered applications.
A curated list of machine learning techniques and resources for cybersecurity professionals.
Introduction to Machine Learning with Python, a book and code repository for learning ML fundamentals.
A Python library for fast, high-quality monocular view synthesis, useful for computer vision and 3D applications.
This GitHub repository is a book on the fundamentals of mathematics, covering topics from basic arithmetic to machine learning, written for developers interested in AI tools and applications.
Evidently is an open-source ML and LLM observability framework to evaluate, test, and monitor AI-powered systems.
This repository contains an efficient implementation of a vision encoding model for vision-language models.
Real-time high-resolution background matting tool for computer vision and ML applications.
OptiScaler bridges upscaling/frame gen across GPUs, supporting DLSS2+, XeSS, FSR2+ and more.
Python code for a book on probabilistic machine learning, with support for various ML frameworks.
Largest list of pre-trained machine learning models for Apple's Core ML framework for iOS 11+.
Open-source observability tool for GenAI and LLM applications, based on OpenTelemetry
A comprehensive reading list for research topics in multimodal machine learning.
Interpret is a framework for fitting interpretable machine learning models and explaining black-box models.
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