AutoGluon: AutoML for Text, Image, and Tabular Data

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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scutjy2015@163.com 版权所有，违权必究 Tan 2018.06

此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。

本项目将《动手学深度学习》（Dive into Deep Learning）原书中的MXNet代码实现改为PyTorch实现。

Code and preprocessed dataset for EMNLP 2019 paper titled "Aspect-based Sentiment Classification with Aspect-specific Graph Convolutional Networks"

Evaluation code for various unsupervised automated metrics for Natural Language Generation.

Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)

Graph Convolutional Networks in PyTorch

PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation

NLP上手教程

PyTorch Tutorial for Deep Learning Researchers

中文命名实体识别（包括多种模型：HMM，CRF，BiLSTM，BiLSTM+CRF的具体实现）

A TensorFlow Implementation of the Transformer: Attention Is All You Need

Natural Language Processing Tutorial for Deep Learning Researchers

Course repo for Applied Natural Language Processing (Spring 2019)

PyTorch tutorials demonstrating modern techniques with readable code

A PyTorch implementation of the Transformer model in "Attention is All You Need".

A PyTorch implementation of Google AI's BERT model provided with Google's pre-trained models, examples and utilities.