How I went from Frontend Dev to Machine Learning Engineer

This book from MIT got me interested in the topic.

I then enrolled in the "Data Scientist with Python" track in DataCamp. I just took a few lessons until I felt I could move on alone.

I bought a copy of the book "Hands-On Machine Learning with Scikit-Learn and TensorFlow" by Aurélien Geron. It was a terrific investment. Read it from cover to cover.

I then worked 3-4 weeks in the good ol' Titanic RMS challenge in Kaggle. Got mediocre results. Didn't care, I was putting the time and sweat. I was learning.

I secretly built an unsolicited news topic classifier for the company I worked for. They didn't like it at all. I felt like they didn't trust me to tackle a Machine Learning project; my value, for them, was doing JavaScript and CSS, nothing else. I moved on.

I won a Udacity scholarship competing in the AWS DeepRacer challenge. The idea was to use Reinforcement Learning to get your autonomous racing car complete 2 laps in the track. (I took this pic with a Nokia 1100)

I enrolled in the Udacity Machine Learning NanoDegree Program. I completed it in a lot more weeks than expected. Got great lessons on how to deploy ML models to production in AWS.

I finally built a hybrid recommender system for one of the biggest crowdfunding sites in Latin America, Vaki Global. Big thanks to Nicolás Contreras for giving me the chance to work on this project. Here's my report:

Curiosity and FOMO helped me add a new skill to my toolbox. I'll keep working on webdev for now, which what I really love doing. I wrote a full post with anecdotes, personal opinions, and key takeaways of my journey learning Machine Learning here: