Feature Engineering Pipelines - Learn Data Science with Travis

Streamlining Feature Engineering Pipelines with Feature-engine

Towards Data Science

In many organizations, we create machine learning models that process a group of input variables to output a prediction. Some of these models predict for example the likelihood of a loan being…

A Framework for Building a Production-Ready Feature Engineering Pipeline

Towards Data Science

Design batch-serving architectures. Use feature stores Code feature engineering pipelines. Build an energy consumption forecaster.

Automate the Feature Engineering Pipeline for Your Relational Dataset

Towards Data Science

Feature engineering is an important and time-consuming component of the data science model development pipeline. The feature engineering pipeline decides the robustness and performance of the model…

Get a Step Ahead With Feature Engineering

Towards Data Science

Machine learning models have difficulty interpreting categorical data; feature engineering allows us to re-contextualize our categorical data to improve the rigor of our machine learning models…

Top Python Packages for Feature Engineering

Towards Data Science

Feature engineering is the process of creating new features from the existing data. Whether we made a simple addition of two columns or combined more than a thousand features, the process is already…

Machine Learning Pipelines: Feature Engineering Numbers

Towards Data Science

A really important part of any machine learning model is the data, especially the features used. In this article, we will go over where feature engineering falls in the machine learning pipeline, and…...

Feature Engineering

Analytics Vidhya

According to a survey in Forbes, data scientists spend 80% of their time on data preparation. This shows the importance of feature engineering in data science. Here are some valuable quotes about…

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…

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…

Best Practices for Feature Engineering

EliteDataScience

Feature engineering, the process creating new input features for machine learning, is one of the most effective ways to improve predictive models. Coming up with features is difficult, time-consuming,...

Feature Factories pt 2: An Introduction to MLFlow

Towards Data Science

If you read my first article you hopefully have a good understanding of what a feature factory is, why it’s important, and a general idea of how to best cultivate one. If you haven’t, I suggest you…

Automated Feature Engineering Tools

Analytics Vidhya

Feature Engineering is a technique to convert raw data columns to something meaningful which can help in predicting the outcomes in a machine learning task. Feature Engineering can be a very tedious…