pchankh Goto Github PK

mtcnn-2

Repository for "Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Neural Networks", implemented with Caffe, C++ interface.

neuroner

Named-entity recognition using neural networks. Easy-to-use and state-of-the-art results.

news-classification

新闻分类系统&谣言处理系统

nmr-pred

Prediction of NMR Spectra from Structure

nmt

TensorFlow Neural Machine Translation Tutorial

nnforge

Convolutional and fully-connected neural networks C++ library. It features CPU and GPU (CUDA) backends

notes

Notes on books, frameworks, languages, sites.

ocan

opendl

The Deep Learning training framework on Spark

oxcvsm

Oxford Compositional Vector Space Models

oxlm

OxLM: Oxford Neural Language Modelling Toolkit

pchankh.github.io

photo-to-3d-model

Collaborator: Andy Feng

places365

The Places365-CNNs

pointnet2

PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

practnlptools

Practical Natural Language Processing Tools for Humans. Dependency Parsing, Syntactic Constituent Parsing, Semantic Role Labeling, Named Entity Recognisation, Shallow chunking, Part of Speech Tagging, all in Python.

prompt-engineering-guide

:octopus: Guides, papers, lecture, and resources for prompt engineering

pseudo-label-keras

Pseudo-Label: Semi-Supervised Learning on CIFAR-10 in Keras

pyfm

Factorization machines in python

pystacknet

pythia

Semantic web oracle.

pytorch-sepconv

an implementation of Video Frame Interpolation via Adaptive Separable Convolution using PyTorch

pytorch-texturegan

TextureGAN in Pytorch

qa

TensorFlow Models for the Stanford Question Answering Dataset

r-net

Tensorflow Implementation of R-Net

r-net-1

A Tensorflow Implementation of R-net: Machine reading comprehension with self matching networks

recipes

Lasagne recipes: examples, IPython notebooks, ...

recommenders

Recommender Systems

restaurant-recommender-system-aws-hadoop-mapreduce

Academic project for Advance Database Management Systems (Big-Data) course

retrocodes

Codes of our team for the OpenAI Retro Contest of reinforcement learning