How to Build an Intuition for Machine Learning Algorithms
Last Updated on December 13, 2019
Machine learning algorithms are complex. To get good at applying a given algorithm you need to study it from multiple perspectives: algorithmic, mathematical and empirical.
It’s this last point I want to stress. You need to build up an intuition or how an algorithm behaves on real data. You need to work on lots of problems.
In this post I want to encourage you to use small in-memory datasets when starting out and when practising machine learning.
Kick-start your project with my new book Master Machine Learning Algorithms, including step-by-step tutorials and the Excel Spreadsheet files for all examples.
Wrapping your head around data
Photo by Nic McPhee, some rights reserved
Study an Algorithm or a Problem, Not Both
You can’t learn a problem and an algorithm at the same time.
If you try, you will progress on both slowly and inefficiently. Your focus will be divided and nether task are being executed ideally.
You will known when you’re in this track because you
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