ML Feature Engineering

Creating Features you own this product

This project is part of the liveProject series ML Feature Engineering and Modeling using Python
prerequisites
intermediate Python • basics of Jupyter Notebook, pandas, and Matplotlib
skills learned
use feature engineering techniques to generate ML features from raw data • data profiling, exploratory data analysis, analyze independent/dependent variables, and visualize data patterns • generate additional features
Jayesh Patel
1 week · 6-8 hours per week · BEGINNER
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Look inside

In this liveProject, you’ll process raw data to make it ready for a machine learning model to diagnose diabetes rates. You’ll use feature engineering techniques to generate ML features from raw data. To make sense of your data, you will undertake data profiling, exploratory data analysis, analyze independent/dependent variables, and visualize data patterns. You’ll evaluate the correlation between dependent and independent variables to identify relevant features. You’ll even generate additional features as needed. Additionally, you will apply feature engineering techniques such as treating missing values and outliers to make your features ready for model training.

This project is designed for learning purposes and is not a complete, production-ready application or solution.

book resources

When you start your liveProject, you get full access to the following books for 90 days.

project author

Jayesh Patel
Jayesh Patel is a strategic big data leader and proven architect who successfully designed complex data processes, architected machine learning pipelines, and developed big data analytics solutions over the past 15+ years. He currently works for Rockstar Games, architecting data-driven big data platforms and artificial intelligence solutions to keep players engaged in Red Dead Redemption II and Grand Theft Auto V. He is an active senior member of the IEEE. His expertise and research in the big data space are well received in numerous international IEEE conferences. He is an editorial board member of a renowned international journal. He actively guides and reviews the research work of other scholars and professors around the world. He completed his master’s from San Diego State University in 2009.

prerequisites

This liveProject is for data scientists who are familiar with Python, the basics of machine learning, and data modeling. To begin this liveProject you will need to be familiar with the following:


TOOLS
  • Intermediate Python
  • Basics of Jupyter Notebook
  • Basics of pandas
  • Basics of Matplotlib
TECHNIQUES
  • Basic file processing
  • Intermediate data processing and feature engineering

you will learn

In this liveProject, you’ll master common Python libraries for the important task of machine learning feature engineering.


  • Data processing with pandas
  • Data visualization with Matplotlib and seaborn
  • ML feature engineering

features

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book resources
Get full access to select books for 90 days. Permanent access to excerpts from Manning products are also included, as well as references to other resources.

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  • Creating Features project for free

team

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  • five seats for your team
  • access to all Manning books, MEAPs, liveVideos, liveProjects, and audiobooks!
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  • choose twelve free products per year
  • exclusive 50% discount on all purchases
  • Creating Features project for free