Bater.Makhabel's Projects
NLP, before and after spaCy
Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.
Compute distance between sequences. 30+ algorithms, pure python implementation, common interface.
Text Content Grapher based on keyinfo extraction by NLP method。输入一篇文档,将文档进行关键信息提取,进行结构化,并最终组织成图谱组织形式,形成对文章语义信息的图谱化展示。
TextRank implementation for Python 3.
This repository includes tutorials on how to use the TensorFlow estimator APIs to perform various ML tasks, in a systematic and standardised way
Some frequently used NLP blocks I implemented
Code for O'Reilly's "A Short Course on TensorFlow"
A collection of deep learning tutorials using Tensorflow and Python
An experimental rasterizer in Tensorflow
Notebooks for my "Deep Learning with TensorFlow 2 and Keras" course
Generic U-Net Tensorflow implementation for image segmentation
FastER RCNN built on tensorflow
Deep learning library featuring a higher-level API for TensorFlow.
RTSeg: Real-time Semantic Segmentation Comparative Study
TFX is an end-to-end platform for deploying production ML pipelines
Tiny Gradient Boosting Tree
本项目曾冲到全球第一,干货集锦见本页面最底部,另完整精致的纸质版《编程之法:面试和算法心得》已在京东/当当上销售
This repository contains a list of all web sites I come across that are either hacked with or purposefully hosting malware, ransomware, viruses or trojans.
A collection of awesome lists, manuals, blogs, hacks, one-liners, cli/web tools and more. Especially for System and Network Administrators, DevOps, Pentesters or Security Researchers.
One has no future if one couldn't teach themself.
This is meant to be a Data Science resource for capturing the latest technology, expertise, and evolving techniques in Data Science.
A list of all named GANs!
The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.
Simple JupyterHub distribution for 1-100 users on a single server
《The Way to Go》中文译本,中文正式名《Go 入门指南》
Magnificent app which corrects your previous console command.
This resource implements a deep neural network through Numpy, and is equipped with easy-to-understand theoretical derivation, mainly for the in-depth understanding of neural networks. 神经网络模型的理论证明与基于Numpy的实现。