souldgxu Goto Github PK

bert

TensorFlow code and pre-trained models for BERT

chinese-word-vectors

100+ Chinese Word Vectors 上百种预训练中文词向量

cnn_finetune

Fine-tune CNN in Keras

d2l-zh

《动手学深度学习》：面向中文读者、能运行、可讨论。英文版即伯克利“深度学习导论”教材。

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

exercise

exercise for nndl

geocoord

**各省市经纬度

hands-on-machine-learning-with-sklearn-tensorflow

handson-ml

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

hedge

Code for the paper "Generating Hierarchical Explanations on Text Classification via Feature Interaction Detection"

hyperopt-sklearn

Hyper-parameter optimization for sklearn

imutils

A series of convenience functions to make basic image processing operations such as translation, rotation, resizing, skeletonization, and displaying Matplotlib images easier with OpenCV and Python.

jieba

结巴中文分词

keras

Deep Learning for humans

keras-cn

Chinese keras documents with more examples, explanations and tips.

keras-demo

keras_deeplearning_example

learngit

learngit-1

教程→ http://t.cn/zQ6LFwE 推送请使用UTF-8编码

machinelearning

My blogs and code for machine learning. http://cnblogs.com/pinard

models

Models and examples built with TensorFlow

new-dand-advanced-china

nlpvisualizationsystem

一个自然语言处理的可视化系统，实现自动生成词云图、文章关键信息提取、多文档主题分布、文本分类等功能，还有一些业务数据的可视化图表展示。

nndl-codes

Sample Codes for NNDL

nndl.github.io

《神经网络与深度学习》 Neural Network and Deep Learning

sakiladatastudio

基于 PyEcharts + Flask + Bootstrap，采用前后端分离模式，生成一个完整的数据可视化系统。数据来源于Sakila样本数据库。

senet

Squeeze-and-Excitation Networks

senta

Baidu's open-source Sentiment Analysis System.

sentiment-analysis-chinese-pytorch

中文的情感分析任务：基于Bi-LSTM+Attention模型，对2万条中文影评数据进行情感分类。Chinese sentiment analysis task: Based on the Bi-LSTM+Attention model, sentiment classification is performed on 20,000 Chinese film review data.

snownlp

Python library for processing Chinese text