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Hey, I want to convince you that you can get started and make great progress in machine learning without being strong in
mathematics.
You can get started in machine learning today, empirically. There are 3 options available to you are:
1. Learn to drive a tool like scikit-learn, R or Weka.
2. Use libraries that provide algorithms and write little programs.
3. Implement algorithms yourself from tutorials and books.
Define small projects, solve them methodically and present the results of what you have learned (such as on your blog). You will
start to build up some momentum following this process.
This will drive you to want (need) to understand how a technique really works. You will dive into mathematical treatments of
algorithms because you passionately need to know, not because someone told you to.
Mathematics is critical to mastering machine learning, but it can come later.
The algorithmic descriptions and applied understanding of machine learning can take you a long way as a practitioner, maybe as far
as you need to go.
Learn more about how you can get started in machine learning without the math in the post:
>> What if I’m Not Good at Mathematics
I’ll speak to you soon.
Jason.
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