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acl2018-semantic-parsing-tutorial

Materials from the ACL 2018 tutorial on neural semantic parsing

ailearning

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

algorithm_interview_notes-chinese

2018/2019/校招/春招/秋招/算法/机器学习(Machine Learning)/深度学习(Deep Learning)/自然语言处理(NLP)/C/C++/Python/面试笔记

allennlp_sempar

Experiments with AllenNLP on semantic parsing datasets

awesome-nlp

:book: A curated list of resources dedicated to Natural Language Processing (NLP)

awesome-pytorch-list

A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

awesome-question-answering

Resources, datasets, papers on Question Answering

bert-as-service

Mapping a variable-length sentence to a fixed-length vector using BERT model

cnn-text-classification-tf

Convolutional Neural Network for Text Classification in Tensorflow

coarse2fine

coding-interview-101

Coding interview tips

compositional-pre-training-for-semantic-parsing-with-bert

Implementation of Semantic Parsing with BERT and compositional pre-training on GeoQuery

decanlp

The Natural Language Decathlon: A Multitask Challenge for NLP

deep-learning-roadmap

:satellite: All You Need to Know About Deep Learning - A kick-starter

deep-learning-with-tensorflow-book

深度学习入门开源书，基于TensorFlow 2.0案例实战。Open source Deep Learning book, based on TensorFlow 2.0 framework.

deeplearning

深度学习入门教程, 优秀文章, Deep Learning Tutorial

deeplearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06

docker-cheat-sheet

Docker Cheat Sheet

ds_project_template

Data Science Project Template

eat_pytorch_in_20_days

Pytorch🍊🍉 is delicious, just eat it! 😋😋

eat_tensorflow2_in_30_days

Tensorflow2.0 🍎🍊 is delicious, just eat it! 😋😋

fairseq

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

ganswer

A KBQA system based on DBpedia.

hands-on-machine-learning

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

introtodeeplearning

Lab Materials for MIT 6.S191: Introduction to Deep Learning

lang2logic-pytorch

PyTorch port of the paper "Language to Logical Form with Neural Attention"

learning-resource

列出一些优秀的程序员学习资源

lihang-code

《统计学习方法》的代码实现

limmersio

Replacement of words for language learning.

ml-in-action-code-and-note

:chart_with_upwards_trend:Machine Learning code in Python3.x. （机器学习实战 py3代码整理）Some notes about the practices:（for reference only）