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Programming Machine Learning
book

Programming Machine Learning

by Paolo Perrotta
March 2020
Beginner to intermediate
342 pages
8h 38m
English
Pragmatic Bookshelf
Content preview from Programming Machine Learning

Hands On: Minesweeper

If you’re up for a challenge, here’s an optional exercise for you: modify the MNIST classifier to run on the Sonar dataset.[15] The Sonar dataset (also known as the “Mines vs. Rocks” dataset) contains the patterns generated by bouncing sonar signals off two different types of objects: metal cylinders (which could potentially be mines) and rocks. See if you can train the classifier to tell apart mines from rocks.

Don’t underestimate this little project. If you’re not steeped in Python, it might take you a few hours to write the Sonar equivalent of the mnist.py library, and you’ll probably need to browse the documentation of both Python and NumPy. Only tackle this exercise if you like the idea of spending some time on it. ...

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Publisher Resources

ISBN: 9781680507706Errata Page