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SAS Tutorial | How to Choose a Machine Learning Algorithm
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With so many machine learning algorithms to choose from, it’s hard to know which one is best for your scenario. In the SAS How To Tutorial, SAS’ Aurora Peddycord-Liu gives pros and cons of some commonly used machine learning models. She then shows how to assess and compare models in SAS Model Studio.
Chapters
0:00 – Overview
0:33 – Step 1: Understand your ingredients
2:09 – Step 2: Match methods to ingredients
2:45 – Pros and cons of decision tree
4:39 – Pros and cons of neural network
6:34 – What deep learning is and what it is not
8:46 – Step 3: Assess results in a systematic approach
9:24 – How to assess results in SAS Model Studio
Download the Data
Learn more about SAS Software
Related Video Tutorials that Aurora Mentions
SUBSCRIBE TO THE SAS USERS YOUTUBE CHANNEL #SASUsers #LearnSAS
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
Chapters
0:00 – Overview
0:33 – Step 1: Understand your ingredients
2:09 – Step 2: Match methods to ingredients
2:45 – Pros and cons of decision tree
4:39 – Pros and cons of neural network
6:34 – What deep learning is and what it is not
8:46 – Step 3: Assess results in a systematic approach
9:24 – How to assess results in SAS Model Studio
Download the Data
Learn more about SAS Software
Related Video Tutorials that Aurora Mentions
SUBSCRIBE TO THE SAS USERS YOUTUBE CHANNEL #SASUsers #LearnSAS
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
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