Popular GitHub Repositories for Recall

Object Detection Metrics. 14 object detection metrics: mean Average Precision (mAP), Average Recall (AR), Spatio-Temporal Tube Average Precision (STT-AP). This project supports different bounding box formats as in COCO, PASCAL, Imagenet, etc.

Tools and recipes to train deep learning models and build services for NLP tasks such as text classification, semantic search ranking and recall fetching, cross-lingual information retrieval, and question answering etc.

A python wrapper for the Doc2X API and comes with native texts processing (to improve PDF recall in RAG). | Doc2X API的python封装，同时附带本地的文本处理(提升PDF在RAG中的召回率)。

Code base for the precision, recall, density, and coverage metrics for generative models. ICML 2020.

[Not Actively Maintained] Whitebox is an open source E2E ML monitoring platform with edge capabilities that plays nicely with kubernetes

RECA is a flexible, lightweight memory and retrieval system designed to empower AI agents with real-time recall, long-term memory, and contextual search.

rec_pangu is a flexible open-source project for recommendation systems. It incorporates diverse AI models like ranking algorithms, sequence recall, multi-interest models, and graph-based techniques. Designed for both beginners and advanced users, it enables rapid construction of efficient, custom recommendation engines.

Force Remove Copilot and Recall in Windows

Play, learn, solve, and analyze No-Limit Texas Hold Em. Implementation follows from Monte Carlo counter-factual regret minimization over with hierarchical K-means imperfect recall abstractions.

Assessing Generative Models via Precision and Recall (official repository)

We start a company-name recognition task with a small scale and low quality training data, then using skills to enhanced model training speed and predicting performance with least artificial participation. The methods we use involve lite pre-training models such as Albert-small or Electra-small with financial corpus, knowledge of distillation and multi-stage learning. The result is that we improve the recall rate of company names recognition task from 0.73 to 0.92 and get 4 times as fast as BERT-Bilstm-CRF model.

??? This one stop project is a complete COVID-19 detection package comprising of 3 tasks: ? Task 1 --> COVID-19 Classification ? Task 2 --> COVID-19 Infection Segmentation ? Task 3 --> Lung Segmentation

Recall to Imagine, a model-based RL algorithm with superhuman memory. Oral (1.2%) @ ICLR 2024

Anomaly detection on the UC Berkeley milling data set using a disentangled-variational-autoencoder (beta-VAE). Replication of results as described in article "Self-Supervised Learning for Tool Wear Monitoring with a Disentangled-Variational-Autoencoder"

PyTorch code for FLD (Feature Likelihood Divergence), FID, KID, Precision, Recall, etc. using DINOv2, InceptionV3, CLIP, etc.

Build Recommender System with PyTorch + Redis + Elasticsearch + Feast + Triton + Flask. Vector Recall, DeepFM Ranking and Web Application.

Quick start. Index multiple documents in a repository using HuggingFace embeddings. Save them in Chroma and / or FAISS for recall. Choose OpenAI or Azure OpenAI APIs to get answers to your questions - Q&A with OpenAI and Azure OpenAI.

The project is a simple sentiment analysis using NLP. The project in written in python with Jupyter notebook. It shows how to do text preprocessing (removing of bad words, stop words, lemmatization, tokenization). It further shows how to save a trained model, and use the model in a real life suitation. The machine learning model used here is k-Nearest Neighbor which is used to build the model. Various performance evaluation techniques are used, and they include confusion matrix, and Scikit-learn libraries classification report which give the accuracy, precision, recall and f1- score preformance of the model. The target values been classified are positive and negative review.

Retrieval-Augmented Generation on PDF for Free, Integrated with Memory to recall previous interactions, it operates as a sophisticated lang-chain application.

Automatic method for the recognition of hand gestures for the categorization of vowels and numbers in Colombian sign language based on Neural Networks (Perceptrons), Support Vector Machine and K-Nearest Neighbor for classifier /// Método automático para el reconocimiento de gestos de mano para la categorización de vocales y números en lenguaje de se?as colombiano basado en redes neuronales (perceptrones), soporte de máquina vectorial y K-vecino más cercano para clasificador