The quality of the predictions coming out of your machine learning model is a direct reflection of the data you feed it during training. Feature engineering helps you extract every last bit of value out of data.
This course provides the tools to take a data set, tease out the signal, and throw out the noise in order to optimize your models. The concepts generalize to nearly any kind of machine learning algorithm. Instructor Derek Jedamski provides a refresher on machine learning basics and a thorough introduction to feature engineering. He explores continuous and categorical features and shows how to clean, normalize, and alter them. Learn how to address missing values, remove outliers, transform data, create indicators, and convert features. In the final chapters, Derek explains how to prepare features for modeling and provides four variations for comparison, so you can evaluate the impact of cleaning, transforming, and creating features through the lens of model performance.
You can enroll in the course (and 15,000+ other courses) for FREE by starting your free trial month at LinkedIn Learning! Click here to enroll in Applied Machine Learning: Feature Engineering.
Get a Certificate of Completion
By successfully completing the course, get a certificate of completion from LinkedIn which you can use to share what you’ve learned, and be a standout professional in your desired industry. The certificate can also be used to:
- Showcase on your LinkedIn profile under the ‘Licenses and Certificate’ section.
- Download or print out a PDF to share with others.
- Share as an image online to demonstrate your skill.