Tianxiang Zhang's repositories
awesome-embedding-models
A curated list of awesome embedding models tutorials, projects and communities.
deep-learning-from-scratch-2
『ゼロから作る Deep Learning ❷』のリポジトリ
deep_learning_theory_and_practice
《深度学习理论与实战：基础篇》代码
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，近30万字。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
gt-nlp-class
Course materials for Georgia Tech CS 4650 and 7650, "Natural Language"
simplified-deeplearning
Simplified implementations of deep learning related works
training-data-analyst
Labs and demos for courses for GCP Training (http://cloud.google.com/training).
awesome-bert
bert nlp papers, applications and github resources ， BERT 相关论文和 github 项目
chameleon_recsys
Source code of CHAMELEON - A Deep Learning Meta-Architecture for News Recommender Systems
FakeNewsCorpus
A dataset of millions of news articles scraped from a curated list of data sources.
ginza
A Japanese NLP Library using spaCy as framework based on Universal Dependencies
Hands-On-Machine-Learning-Using-Amazon-SageMaker-v-
Hands-On Machine Learning Using Amazon SageMaker [video], published by Packt
jh-kaggle-util
Jeff Heaton's Kaggle Utilities
keras-bert
A simple technique to integrate BERT from tf hub to keras
keras-bert-1
Implementation of BERT that could load official pre-trained models for feature extraction and prediction
keras-elmo
How to use ELMo embeddings in Keras with Tensorflow Hub
magnitude
A fast, efficient universal vector embedding utility package.
ProgrammingBooks
用于收集编程书籍及笔记，喜欢请点击右上角"Star"或"Fork"支持一下！！！
sars_tutorial
Repository for the tutorial on Sequence-Aware Recommender Systems held at ACM RecSys 2018
state-of-the-art-result-for-machine-learning-problems
This repository provides state of the art (SoTA) results for all machine learning problems. We do our best to keep this repository up to date. If you do find a problem's SoTA result is out of date or missing, please raise this as an issue or submit Google form (with this information: research paper name, dataset, metric, source code and year). We will fix it immediately.
sumy
Module for automatic summarization of text documents and HTML pages.