yajwang Goto Github PK

100-pandas-puzzles

100 data puzzles for pandas, ranging from short and simple to super tricky (60% complete)

anly530_group1classproject

Machine Learning 1 Course Project

anly530_group1lab2

Machine Learning 1 Laboratory2

anly530_group1lab3

anly560hu

awesome-bayes

List of resources for bayesian inference

awesome-data-comp-solution

数据科学/人工智能比赛解决方案汇总

awesome-database-learning

A list of learning materials to understand databases internals

awesome-interview

Collection of awesome interview references.

awesome-production-machine-learning

A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

awesome-recommender-systems

A curated list of awesome resources about Recommender Systems.

awesome-recsys

A curated list of awesome Recommender System (Books, Conferences, Researchers, Papers, Github Repositories, Useful Sites, Youtube Videos)

business-machine-learning

A curated list of practical business machine learning (BML) and business data science (BDS) applications for Accounting, Customer, Employee, Legal, Management and Operations.

coding-interview-university

A complete computer science study plan to become a software engineer.

collaborativememorynetwork

Collaborative Memory Network for Recommendation Systems, SIGIR 2018

data-science-interview-resources

A repository listing out the potential sources which will help you in preparing for a Data Science/Machine Learning interview. New resources added frequently.

data-science-interviews

Data science interview questions and answers

deep-learning-for-recommendation-systems

This repository contains Deep Learning based articles , paper and repositories for Recommender Systems

deep-recurrent-attention-writer

An implementation of DRAW (Deep Recurrent Attention Writer) and VAE(Variational Auto-Encoder)

deeplearning

Deep Learning introduction and its application in various fields

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[email protected] 版权所有，违权必究 Tan 2018.06

draw

TensorFlow Implementation of "DRAW: A Recurrent Neural Network For Image Generation"

econml

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

forecasting

Time Series Forecasting Best Practices & Examples

gain

Generative Adversarial Imputation Networks (GAIN)

generative-adversarial-network-tutorial

Tutorial on creating your own GAN in Tensorflow

generative-adversarial-networks-roadmap

The Roadmap to Learn Generative Adversarial Networks (GANs)

generative-models

Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.

handwriting-generation

Implementation of handwriting generation with use of recurrent neural networks in tensorflow. Based on Alex Graves paper (https://arxiv.org/abs/1308.0850).

industry-machine-learning

A curated list of applied machine learning and data science notebooks and libraries across different industries.