Popular GitHub Repositories for Cell Type Annotation

A lightning-fast search engine API bringing AI-powered hybrid search to your sites and applications.

Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale.

The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

Open source annotation tool for machine learning practitioners.

Effortless data labeling with AI support from Segment Anything and other awesome models.

Argilla is a collaboration tool for AI engineers and domain experts to build high-quality datasets

Visual Object Tagging Tool: An electron app for building end to end Object Detection Models from Images and Videos.

Type less, code more: Cody is an AI code assistant that uses advanced search and codebase context to help you write and fix code.

Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier

? Turns your machine learning code into microservices with web API, interactive GUI, and more.

A fast type checker and IDE for Python

? A refreshing functional take on deep learning, compatible with your favorite libraries

This repository contains a reading list of papers on Time Series Forecasting/Prediction (TSF) and Spatio-Temporal Forecasting/Prediction (STF). These papers are mainly categorized according to the type of model.

Images to inference with no labeling (use foundation models to train supervised models).

A Burp Suite extension that integrates OpenAI's GPT to perform an additional passive scan for discovering highly bespoke vulnerabilities and enables running traffic-based analysis of any type.

A full-body keyboard using gestures to type through computer vision

The AI Datastore for Schemas, BLOBs, and Predictions. Use with your apps or integrate built-in Human Supervision, Data Workflow, and UI Catalog to get the most value out of your AI Data.

Learn Japanese grammar with TypeScript

scAR (single-cell Ambient Remover) is a deep learning model for removal of the ambient signals in droplet-based single cell omics

The data scientist's open-source choice to scale, assess and maintain natural language data. Treat training data like a software artifact.