Hilary Mason: An Intro to Machine Learning with Web Data

Once you've accumulated a pile of data through your web application, what do you do with it? In this insightful video course, bit.ly lead scientist Hilary Mason shows you how to solve data analysis problems using basic machine learning techniques and frameworks. You'll follow several examples through the entire process and all the machine learning techniques—from obtaining, cleaning, and exploring data to building a model and interpreting the results.

Examine several real-world analysis solutions, including supervised learning about machine learning techniques and classification, unsupervised learning and clustering, and building common machine learning applications such as recommendation systems. If you're a developer interested in the math and processes necessary to apply machine learning techniques to web data, this video course is for you.

About the Author

Hilary Mason

Hilary Mason is the lead scientist at bit.ly, where she is finding sense in vast data sets. She is a former computer science professor with a background in machine learning techniques and data mining, has published numerous academic papers, and regularly releases code on her personal site, www.hilarymason.com.

She has discovered two new species, loves to bake cookies, and asks way too many questions.

• Over 5 lectures and 2.5 hours of content!
• Solve data analysis problems using basic machine learning techniques and frameworks.
• You'll follow several examples through the entire process—from obtaining, cleaning, and exploring data to building a model and interpreting the results.

This class is intended for developers who are interested in an introduction to the math and processes to apply machine learning techniques to web data.

You should be able to write code but do not need formal mathematics training.

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