3 Reasons Why You Shouldn’t Worry About Math for Your Machine Learning Journey

And How to Still Achieve Success

Image by marker_photography from Pixabal.com

It All Started From My Personal Struggle

To tell you the truth, the fear of not being good enough at math has been hunting me from day one when I started my Machine Learning journey. It first struck me when I tried to apply the chain-rule while doing the back-propagation of neural networks. It took me a good several days before the assignment deadline until I finally figured out how to calculate the gradients. Man, that felt hard! I can almost still taste the bitterness and hardship in my mouth. Little did I know, this probably was the easy part. The real nightmare started when I first try to read a machine learning paper… 🤮

If you can relate to my experience, you’ve been there. What I am trying to tell you today is: It doesn’t need to be that way, and you can have a totally different angle to approach your machine learning journey, without worry too much about math. Let me explain.

Math Needed for Applied Deep Learning is very Limited

In Machine Learning, too many people have the impostor syndrome of not being able to get to the bottom of the math behind the model. It’s understandable, and we…