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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

Lesson 1: Batch Serving. Feature Stores. Feature Engineering Pipelines. Continue reading on Towards Data Science

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…

Automate the Feature Engineering Pipeline for Your Relational Dataset

Towards Data Science

Essential guide to an open-source Python framework for automated feature engineering Continue reading on Towards Data Science

Top Python Packages for Feature Engineering

Towards Data Science

Know these packages to improve your data workflow Continue reading on Towards Data Science

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…

4 Python Libraries for Automated Feature Engineering That You Should Use in 2023

Level Up Coding

Use these frameworks to empower your machine-learning work Mikael Blomkvist photo: https://www.pexels.com/zh-cn/photo/6476254/ “Feature Engineering” refers to the use of domain knowledge and existing...

4 Tips for Advanced Feature Engineering and Preprocessing

Towards Data Science

Arguably, two of the most important steps in developing a machine learning model is feature engineering and preprocessing. Feature engineering consists of the creation of features whereas…

Automating ML Feature Engineering

Towards Data Science

One of the biggest challenges in machine learning workflows is identifying which inputs in your data will provide the best signals for training predictive models. For image data and other…

3 Fundamental Processes in Feature Engineering

Towards Data Science

Presenting data patterns to models the right way Continue reading on Towards Data Science

A Hands-On Guide to Automated Feature Engineering in Python

Analytics Vidhya

Anyone who has participated in machine learning hackathons and competitions can attest to how crucial feature engineering can be. It is often the difference between getting into the top 10 of the…

Automated Feature Engineering in Python

Towards Data Science

Machine learning is increasingly moving from hand-designed models to automatically optimized pipelines using tools such as H20, TPOT, and auto-sklearn. These libraries, along with methods such as…

Review of “Feature Engineering Made Easy”

Python in Plain English

https://drive.google.com/file/d/1RfhNUOXjuIm3-Cjs5l5EjQtmKJM-O8SE/view?usp=sharing Feature Engineering Made Easy is an essential read for data scientists and machine learning enthusiasts looking to de...

Mastering Feature Engineering in Python

Python in Plain English

Transforming Raw Data into Powerful Predictors Continue reading on Python in Plain English

Feature Engineering — Unraveling the Mystery

Towards Data Science

Data Science | Machine Learning | Feature Engineering Feature Engineering — Unraveling the Mystery What is feature engineering, the problem it solves, and why it really matters Theoretically or pract...

Discover Feature Engineering, How to Engineer Features and How to Get Good at It

Machine Learning Mastery

Last Updated on August 15, 2020 Feature engineering is an informal topic, but one that is absolutely known and agreed to be key to success in applied machine learning. In creating this guide I went wi...

Feature Engineering in Python

Towards Data Science

In my decade plus as a data scientist, my experience largely agrees with Andrew Ng’s statement, “Applied machine learning is basically feature engineering.” From the very start of my career, building…...

The Power of Feature Engineering

Towards Data Science

Using feature engineering to model non-linear decision boundaries with logistic regression. A good alternative to more complicated machine learning models.