yolo目标检测算法

LLM inference in C/C++

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…

DoTAT 是一款基于web、面向领域的通用文本标注工具，支持大规模实体标注、关系标注、事件标注、文本分类、基于字典匹配和正则匹配的自动标注以及用于实现归一化的标准名标注，同时也支持迭代标注、嵌套实体标注和嵌套事件标注。标注规范可自定义且同类型任务中可“一次创建多次复用”。通过分级实体集合扩大了实体类型的规模，并设计了全新高效的标注方式，提升了用户体验和标注效率。此外，本工具增加了审核环节，…

java automatic derivation

image retrieval

linUCB

automatic event extract

CVPR 2018: Structure Inference Net for Object Detection

Data competition Top Solution 数据竞赛top解决方案开源整理

100+ Chinese Word Vectors 上百种预训练中文词向量

C++ High Performance, published by Packt

Deeplearning4j Examples (DL4J, DL4J Spark, DataVec)

基于工作流的Python脚本引擎，从此写代码就像做填空题 ~

爬取今日头条，网易，腾讯等新闻,并建立简单的搜索引擎

Python tools for supervised learning by Quantum Neural Networks

FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

A little word cloud generator in Python

A platform for community discussion. Free, open, simple.

图解tensorflow 源码

Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

scikit-learn: machine learning in Python

DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.

Deep Reinforcement Learning for Keras.

Caffe2 is a lightweight, modular, and scalable deep learning framework.

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow

Code for the paper "Generative Adversarial Imitation Learning"

Learning Multi-Domain Convolutional Neural Networks for Visual Tracking

A recommender systems development and evaluation package by Mendeley