absatasy,github

Simple, Keras-powered multilingual NLP framework, allows you to build your models in 5 minutes for named entity recognition (NER), part-of-speech tagging (PoS) and text classification tasks. Includes BERT, GPT-2 and word2vec embedding.

keras-bert

Implementation of BERT that could load official pre-trained models for feature extraction and prediction

keras-yolo3

Training and Detecting Objects with YOLO3

keras-yolo3-1

A Keras implementation of YOLOv3 (Tensorflow backend)

learnpython

以撸代码的形式学习Python

leetcodeanimation

Demonstrate all the questions on LeetCode in the form of animation.（用动画的形式呈现解LeetCode题目的思路）

leetcodebypython

The python codes for LeetCode

lihang-code

《统计学习方法》的代码实现

ludwig

Ludwig is a toolbox built on top of TensorFlow that allows to train and test deep learning models without the need to write code.

manim

Animation engine for explanatory math videos

medicalnamedentityrecognition

Medical Named Entity Recognition implement using bi-directional lstm and crf model with char embedding.CCKS2017中文电子病例命名实体识别项目,主要实现使用了基于字向量的四层双向LSTM与CRF模型的网络.该项目提供了原始训练数据样本(一般醒目,出院情况,病史情况,病史特点,诊疗经过)与转换版本,训练脚本,预训练模型,可用于序列标注研究.把玩和PK使用.

medicalnet

Many studies have shown that the performance on deep learning is significantly affected by volume of training data. The MedicalNet project provides a series of 3D-ResNet pre-trained models and relative code.