solegalli

feature-engineering-for-machine-learning

Code repository for the online course Feature Engineering for Machine Learning

feature-selection-for-machine-learning

Code repository for the online course Feature Selection for Machine Learning

machine-learning-imbalanced-data

Code repository for the online course Machine Learning with Imbalanced Data

hyperparameter-optimization

Code repository for the online course Hyperparameter Optimization for Machine Learning

feature_engine

Feature engineering package with sklearn like functionality

packt_featureengineering_cookbook

DataTalks.Club2022

deploying-machine-learning-models

Example Repo for the Udemy Course "Deployment of Machine Learning Models"

feature-selection-in-machine-learning-book

Code repository for the book feature selection in machine learning

ingenieria-de-variables

feature-selection-with-feature-engine-book

Code repository for the book Feature engineering with Feature-engine

machine-learning-interpretability

Python-Feature-Engineering-Cookbook-Second-Edition

udemy-feml-challenge

Amazing-Feature-Engineering

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.

solegalli

imbalanced-learn

A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning

tsfresh

Automatic extraction of relevant features from time series:

PyALE

ALE Plots with python

skforecast

Time series forecasting with scikit-learn models

sktime

A unified framework for machine learning with time series