lujunsincerely,Lu Jun,github

ai-job-recommend

国内公司人工智能方向（含机器学习、深度学习、计算机视觉和自然语言处理）岗位的招聘信息（含全职、实习和校招）

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

awesome-ml-for-cybersecurity

:octocat: Machine Learning for Cyber Security

contextualbandits

Python implementations of contextual bandits algorithms

conv_seq2seq

A tensorflow implementation of Fairseq Convolutional Sequence to Sequence Learning(Gehring et al. 2017)

deep-reinforcement-learning-with-python

Master classic RL, deep RL, distributional RL, inverse RL, and more using OpenAI Gym and TensorFlow with extensive Math

deepctr

Easy-to-use,Modular and Extendible package of deep-learning based CTR models.

deepgbm

Implementation for the paper "DeepGBM: A Deep Learning Framework Distilled by GBDT for Online Prediction Tasks", which has been accepted by KDD'2019.

deepmatch

A deep matching model library for recommendations & advertising. It's easy to train models and to export representation vectors which can be used for ANN search.

deepmf

DeepMF: Deciphering the Latent Patterns in Omics Profiles with a Deep Learning Method

dlrm

An implementation of a deep learning recommendation model (DLRM)

flowtron

Flowtron is an auto-regressive flow-based generative network for text to speech synthesis with control over speech variation and style transfer

focalloss_keras

Focal Loss implementation by Keras with TensorFlow backend

ga3c

Hybrid CPU/GPU implementation of the A3C algorithm for deep reinforcement learning.

graphembedding

Implementation and experiments of graph embedding algorithms.

gst-tacotron2

Mellotron: a multispeaker voice synthesis model based on Tacotron 2 GST that can make a voice emote and sing without emotive or singing training data

hashingdeeplearning

Codebase for "SLIDE : In Defense of Smart Algorithms over Hardware Acceleration for Large-Scale Deep Learning Systems"

keras-recommendation

Using Keras to implement recommender systems

A fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. It is under the umbrella of the DMTK(http://github.com/microsoft/dmtk) project of Microsoft.

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