133 Open source projects that are alternatives of or similar to clink

Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.

A curated list of resources dedicated to Feature Engineering Techniques for Machine Learning

Feature Store for Machine Learning

(deprecated) A fast and memory-efficient Python data engineering framework for machine learning.

Feature engineering package with sklearn like functionality

A recommender system for discovering GitHub repos, built with Apache Spark

An open source python library for automated feature engineering

📖 [译] 面向机器学习的特征工程

本人多次机器学习与大数据竞赛Top5的经验总结，满满的干货，拿好不谢

A collection of non-residential buildings for performance analysis and algorithm benchmarking

A curated list of feature engineering techniques for image and text machine learning

使用sklearn做特征工程

R package for automation of machine learning, forecasting, feature engineering, model evaluation, model interpretation, data generation, and recommenders.

Comprehensive toolkit for generating various numerical features of protein sequences

LAMA - automatic model creation framework

Feature exploration for supervised learning

“魔镜杯”风控算法大赛 拍拍贷风控模型，接近冠军分数

Features selector based on the self selected-algorithm, loss function and validation method

Stock for Deep Learning and Machine Learning

A collection of demos showcasing automated feature engineering and machine learning in diverse use cases

A Python library for easy data analysis, visualization, exploration and modeling

Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.

A hyperparameter optimization and data collection toolbox for convenient and fast prototyping of machine-learning models.

An efficient open-source AutoML system for automating machine learning lifecycle, including feature engineering, neural architecture search, and hyper-parameter tuning.

Data transformations for the ML era

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

A miniature lisp-like language for querying JSON-like structures. Tuned for clientside ML feature extraction.

TransmogrifAI (pronounced trăns-mŏgˈrə-fī) is an AutoML library for building modular, reusable, strongly typed machine learning workflows on Apache Spark with minimal hand-tuning

Analyzing the Drugs Descriptions, conditions, reviews and then recommending it using Deep Learning Models, for each Health Condition of a Patient.

An intuitive library to extract features from time series

Automated Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning 🚀

This is a comprehensive ML techniques with python: Define the Problem- Specify Inputs & Outputs- Data Collection- Exploratory data analysis -Data Preprocessing- Model Design- Training- Evaluation

Automated Deep Learning without ANY human intervention. 1'st Solution for AutoDL [email protected]

Flexible time series feature extraction & processing

Kaggle：Quora Question Pairs, 4th/3396 (https://www.kaggle.com/c/quora-question-pairs)

EvalML is an AutoML library written in python.

Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries

Automated feature engineering for geospatial data

Code for Kaggle Data Science Competitions

Complete-Life-Cycle-of-a-Data-Science-Project

A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.

This is a project based on the FIFA World Cup 2019 and Analyzes the Performance and Efficiency of Teams, Players, Countries and other related things using Data Analysis and Data Visualizations

Open solution to the Home Credit Default Risk challenge 🏡

A New, Interactive Approach to Learning Data Science

DeltaPy - Tabular Data Augmentation (by @firmai)

汉字字符特征提取器 (featurizer)，提取汉字的特征（发音特征、字形特征）用做深度学习的特征 ｜ A Chinese character feature extractor, which extracts the features of Chinese characters (pronunciation features, glyph features) as features for deep learning

This repository contains the code related to Natural Language Processing using python scripting language. All the codes are related to my book entitled "Python Natural Language Processing"

[UNMAINTAINED] Automated machine learning for analytics & production

No description or website provided.

Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.

Prosto is a data processing toolkit radically changing how data is processed by heavily relying on functions and operations with functions - an alternative to map-reduce and join-groupby

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

This repository contains instructions and code to deploy a customer 360 profile solution on Azure stack using the Cortana Intelligence Suite.

A practical feature engineering handbook

There are plenty of courses and tutorials that can help you learn machine learning from scratch but here in GitHub, I want to solve some Kaggle competitions as a comprehensive workflow with python packages. After reading, you can use this workflow to solve other real problems and use it as a template.

feng - feature engineering for machine-learning champions

Using Kaggle Data and Real World Data for Data Science and prediction in Python, R, Excel, Power BI, and Tableau.

Code for Kaggle and Offline Competitions

Linear Prediction Model with Automated Feature Engineering and Selection Capabilities

Default risk prediction for Home Credit competition - Fast, scalable and maintainable SQL-based feature engineering pipeline