SignUpIntroduction to Machine Learning for Coders
Other, , Prof. Jeremy Howard
Updated On 02 Feb, 19
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Other, , Prof. Jeremy Howard
Updated On 02 Feb, 19
Learn the most important machine learning models, including how to create them yourself from scratch, as well as key skills in data preparation, model validation, and building data products.
4.1 ( 11 )
Today well see how to read a much larger dataset - one which may not even fit in the RAM on your machine! And well also learn how to create a random forest for that dataset. We also discuss the software engineering concept of "profiling", to learn how to speed up our code if its not fast enough - especially useful for these big datasets.
Next, we do a deeper dive in to validation sets, and discuss what makes a good validation set, and we use that discussion to pick a validation set for this new data.
In the second half of this lesson, we look at "model interpretation" - the critically important skill of using your model to better understand your data. Todays focus for interpretation is the "feature importance plot", which is perhaps the most useful model interpretation technique.
Sam
Sep 12, 2018
Excellent course helped me understand topic that i couldn't while attendinfg my college.
Dembe
March 29, 2019
Great course. Thank you very much.
