Machine learning is everywhere, and many companies have models up and running. However, developers are always looking at ways to improve model performance. In this SAS How To Tutorial, Bart Baesens shares three tips to improve your models: feature engineering, innovative sources of data, and profit-driven machine learning. Bart’s insights are based on years of research and industry experience across the globe.

Chapters
00:00 – Introduction
02:38 – Overview
04:20 – Machine learning model requirements
07:39 – Bart’s top 4 machine learning models
10:23 – Secret 1: Feature Engineering
12:20 – Feature Engineering Defined
16:08 – Yeo Johnson Transformation
19:01 – Performance Optimization
22:21 – Secret 2: Innovative Sources of Data
23:43 – Call detail record data
27:52 – Secret 3: Profit Driven Machine Learning
34:07 – More ways to learn with SAS training

Additional resources
www.dataminingapps.com (Bart’s site)
www.bluecourses.com (Bart’s online learning platform)

Resource Hub for Data Professionals – https://www.sas.com/sas/offers/resource-hub/roles/data-professional.html?utm_source=youtube.com&utm_medium=referral&utm_campaign=sgf-4406690&utm_content=WTshKY5eDNs

Learn more about SAS Software
Predictive Analytics and Machine Learning Courses –https://support.sas.com/training/us/paths/paml.html
Contact SAS® – https://www.sas.com/en_us/contact.geo.html?utm_source=youtube.com&utm_medium=referral&utm_campaign=sgf-4406690&utm_content=WTshKY5eDNs

SUBSCRIBE TO THE SAS USERS YOUTUBE CHANNEL #SASUsers #LearnSAS
https://www.youtube.com/SASUsers?sub_confirmation=1

ABOUT SAS
SAS is a trusted analytics powerhouse for organizations seeking immediate value from their data. A deep bench of analytics solutions and broad industry knowledge keep our customers coming back and feeling confident. With SAS®, you can discover insights from your data and make sense of it all. Identify what’s working and fix what isn’t. Make more intelligent decisions. And drive relevant change.

CONNECT WITH SAS
SAS ► https://www.sas.com/contact
SAS Customer Support ► https://support.sas.com
SAS Communities ► https://communities.sas.com
SAS Analytics Explorers ► https://explorers.sas.com
Facebook ► https://www.facebook.com/SASsoftware
Twitter ► https://www.twitter.com/SASsoftware
LinkedIn ► https://www.linkedin.com/company/sas
Blogs ► https://blogs.sas.com
RSS ►https://www.sas.com/rss

source