AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP

The official repo of Qwen (通义千问) chat & pretrained large language model proposed by Alibaba Cloud.

Methods to soundly verify deep neural networks

An open source flight dynamics & control software library

Apache Spark - A unified analytics engine for large-scale data processing

To make it easy to benchmark AI accelerators

BigDL: Distributed Deep Learning Framework for Apache Spark

中英文敏感词、语言检测、中外手机/电话归属地/运营商查询、名字推断性别、手机号抽取、身份证抽取、邮箱抽取、中日文人名库、中文缩写库、拆字词典、词汇情感值、停用词、反动词表、暴恐词表、繁简体转换、英文模拟中文发音、汪峰歌词生成器、职业名称词库、同义词库、反义词库、否定词库、汽车品牌词库、汽车零件词库、连续英文切割、各种中文词向量、公司名字大全、古诗词库、IT词库、财经词库、成语词库、地名词库、…

Datafaker is a large-scale test data and flow test data generation tool. Datafaker fakes data and inserts to varied data sources. 测试数据生成工具

Yahoo! Cloud Serving Benchmark

Attacks Which Do Not Kill Training Make Adversarial Learning Stronger (ICML2020 Paper)

Python implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"

A curated list of awesome READMEs

This repository contains implementations and illustrative code to accompany DeepMind publications

architectures and pre-trained models for long document classification.

Pre-Training with Whole Word Masking for Chinese BERT（中文BERT-wwm系列模型）

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

Models and examples built with TensorFlow

This project is special for SemEval2020 task4 Commonsense Validation and Explanantion

This is just a simple Simulink file that is Communicating with X-Plane using UDP Protocol in real time. This project will be updated as my Youtube tutorials continues.

Mesh TensorFlow: Model Parallelism Made Easier

Source code of paper "BP-Transformer: Modelling Long-Range Context via Binary Partitioning"

Collections of Chinese NLP corpus

Source code and dataset for ACL 2019 paper "ERNIE: Enhanced Language Representation with Informative Entities"