liuyaohua2017's repositories
blog
Junnplus's technology blog
DeepLearning-1
深度学习入门教程, 优秀文章, Deep Learning Tutorial
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，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
SparrowRecSys
A Deep Learning Recommender System
Word-Embedding
Word2vec, Fasttext, Glove, Elmo, Bert, Flair pre-train Word Embedding
daisyRec
A developing recommender system in pytorch. Algorithm: KNN, LFM, SLIM, NeuMF, FM, DeepFM, VAE and so on, which aims to fair comparison for recommender system benchmarks
GraphEmbedding
Implementation and experiments of graph embedding algorithms.
pytorch-widedeep
A flexible package to combine tabular data with text and images using Wide and Deep models in Pytorch
CenterNet
Object detection, 3D detection, and pose estimation using center point detection:
PSGAN
PyTorch code for "PSGAN: Pose and Expression Robust Spatial-Aware GAN for Customizable Makeup Transfer" (CVPR 2020 Oral)
cpython
The Python programming language
Python
All Algorithms implemented in Python
camel
Apache Camel is an open source integration framework that empowers you to quickly and easily integrate various systems consuming or producing data.
Surprise
A Python scikit for building and analyzing recommender systems
auto-sklearn
Automated Machine Learning with scikit-learn
scikit-learn
scikit-learn: machine learning in Python
camelinaction2
:camel: This project hosts the source code for the examples of the Camel in Action 2nd ed book :closed_book: written by Claus Ibsen and Jonathan Anstey.
numpy
The fundamental package for scientific computing with Python.
scipy
Scipy library main repository
xlearn
High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.
numpy-ml
Machine learning, in numpy
KnowledgeGraphCourse
东南大学《知识图谱》研究生课程
DeepLearning
Python for《Deep Learning》，该书为《深度学习》(花书) 数学推导、原理剖析与源码级别代码实现
Reco-papers
Classic papers and resources on recommendation
lihang-code
《统计学习方法》的代码实现
featuretools
An open source python library for automated feature engineering
Statistical-Learning-Method_Code
手写实现李航《统计学习方法》书中全部算法
ML-NLP
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。