309 Open source projects that are alternatives of or similar to featurewiz

This repository consist of a 50-day program. All the statistics required for the complete understanding of data science will be uploaded in this repository.

Exemplary, annotated machine learning pipeline for any tabular data problem.

Feature engineering package with sklearn like functionality

Flexible time series feature extraction & processing

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

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

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

[UNMAINTAINED] Automated machine learning for analytics & production

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"

DeltaPy - Tabular Data Augmentation (by @firmai)

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

Fast k-Nearest Neighbors Classifier for Large Datasets

Data transformations for the ML era

Material of the Kaggle Berlin meetup group!

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

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.

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

Versatile Nonlinear Feature Selection Algorithm for High-dimensional Data

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.

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

An intuitive library to extract features from time series

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.

Market Mix Modelling for an eCommerce firm to estimate the impact of various marketing levers on sales

skrobot is a Python module for designing, running and tracking Machine Learning experiments / tasks. It is built on top of scikit-learn framework.

Comprehensive toolkit for generating various numerical features of protein sequences

Automatic feature engineering using deep learning and Bayesian inference using TensorFlow.

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

A simplified version of featuretools for Spark

Library for multi-dimensional, multi-sensor, uni/multivariate time series data analysis, unsupervised feature selection, unsupervised deep anomaly detection, and prototype of explainable AI for anomaly detector

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

Stock for Deep Learning and Machine Learning

Top 5th percentile solution to the Kaggle knowledge problem - Bike Sharing Demand

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

Open solution to the Home Credit Default Risk challenge 🏡

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

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

Automatic feature engineering using Generative Adversarial Networks using TensorFlow.

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

NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.

Automatic machine learning for tabular data. ⚡🔥⚡

This package can be used for dominance analysis or Shapley Value Regression for finding relative importance of predictors on given dataset. This library can be used for key driver analysis or marginal resource allocation models.

A FEAture Selection Toolbox for C/C+, Java, and Matlab/Octave.

Serverless Inferencing on Kubernetes

Understanding transportation mode from GPS (Global Positioning System) traces is an essential topic in the data mobility domain. In this paper, a framework is proposed to predict transportation modes. This framework follows a sequence of five steps: (i) data preparation, where GPS points are grouped in trajectory samples; (ii) point features gen…

Top 1% rankings (22/3270) code sharing for Kaggle competition Sberbank Russian Housing Market: https://www.kaggle.com/c/sberbank-russian-housing-market

This repo provides projects on deep-learning mainly using Tensorflow 2.0

Trading Algorithm by XGBoost

Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.

Framework to build your own reverse image search engine

A basic framework for pulmonary nodule detection and characterization in CT

A package to integrate rollout into your Laravel project.

Engine X - 实时AI智能决策引擎、规则引擎、风控引擎、数据流引擎。 通过可视化界面进行规则配置，无需繁琐开发，节约人力，提升效率，实时监控，减少错误率，随时调整； 支持规则集、评分卡、决策树，名单库管理、机器学习模型、三方数据接入、定制化开发等；

An in-depth analysis of audio classification on the RAVDESS dataset. Feature engineering, hyperparameter optimization, model evaluation, and cross-validation with a variety of ML techniques and MLP

The complete code and notebooks used for the ACM Recommender Systems Challenge 2019

Machine Learning Operator & Controller for Kubernetes

Woodwork is a Python library that provides robust methods for managing and communicating data typing information.

A schema-aware Scala library for data transformation

🔥 Fast, simple sklearn-like feature processing for Go