Feature Versioning - Learn Data Science with Travis

Feature Engineering

Towards Data Science

Feature engineering is a set of techniques applied in data science aiming to make sure the data can be used properly by models. It is a mix between science and art, and is arguably the most important…...

Feature Engineering using Featuretools with code

Analytics Vidhya

Feature engineering, also known as feature creation, is the process of constructing new features from existing data to train a machine learning model. Typically, feature engineering is a drawn-out…

Feature engineering A-Z

Towards Data Science

Feature engineering is the process of transforming data to extract valuable information. In fact, if appropriately transformed, feature engineering can play even a bigger role in model performance…

Let’s Do: Feature Engineering

Towards Data Science

Feature engineering can mean different things to different people, but the term largely covers the process of identifying, manipulating, and transforming information in order to improve the…

Branches Are All You Need: Our Opinionated ML Versioning Framework

Towards Data Science

A practical approach to versioning machine learning projects using Git Branches that simplifies workflows and organises data and models TL;DR A simple approach to versioning machine learning projects...

Stop One-Hot Encoding your Time-based Features

Towards Data Science

Feature Engineering is an essential component of the data science model development pipeline. A data scientist spends most of the time analyzing and preparing features to train a robust model. A raw…

Feature Engineering — deep dive into Encoding and Binning techniques

Towards Data Science

Feature engineering is the most important aspect of a data science model development. There are several categories of features in a raw dataset. Features can be text, date/time, categorical, and…

Use semantic versioning

Java Best Practices

Semantic versioning is a well-specified convention used by many software projects, although admittedly the extent to which the convention is followed can vary considerably between projects. In essenc...

Use semantic versioning

Java Best Practices

Semantic versioning is a well-specified convention used by many software projects, although admittedly the extent to which the convention is followed can vary considerably between projects. In essence...

Feature Engineering Techniques

Towards Data Science

Feature engineering is one of the key steps in developing machine learning models. This involves any of the processes of selecting, aggregating, or extracting features from raw data with the aim of…

Feature Engineering on Date-Time Data

Towards Data Science

According to Wikipedia, feature engineering refers to the process of using domain knowledge to extract features from raw data via data mining techniques. These features can then be used to improve…

Feature Engineering Examples: Binning Numerical Features

Towards Data Science

Feature engineering focuses on using the variables already present in your dataset to create additional features that are (hopefully) better at representing the underlying structure of your data. For…...