Feature Engineering for Machine Learning in Python
|
Create new features to improve the performance of your Machine Learning models.
Every day you read about the amazing breakthroughs in how the newest applications of machine learning are changing the world. Often this reporting glosses over the fact that a huge amount of data munging and feature engineering must be done before any of these fancy models can be used. In this course, you will learn how to do just that. You will work with Stack Overflow Developers survey, and historic US presidential inauguration addresses, to understand how best to preprocess and engineer features from categorical, continuous, and unstructured data. This course will give you hands-on experience on how to prepare any data for your own machine learning models.
User Reviews
Be the first to review “Feature Engineering for Machine Learning in Python”
Related Products
LLMOps: Building Real-World Applications With Large Language Models
Learn to deploy and optimize applications utilizing large language models for natural language processing.
Machine Learning: Random Forests & Decision Trees
Learn how to build decision trees and then build those trees into random forests.
Machine Learning: Introduction with Regression
Get started with machine learning and learn how to build, implement, and evaluate linear regression models.
Machine Learning/AI Engineer
Machine Learning/AI Engineers build end-to-end ML applications and power many of the apps we use every day. They work in Python, Git, & ML.
Intermediate Machine Learning
Level up your machine learning skills with tuning methods, advanced models, and dimensionality reduction.
Intro to Language Models in Python
Build the basic language models in Python.
There are no reviews yet.