A Roadmap to Become a Machine Learning Engineer
As a Machine Learning Engineer, I remember feeling uncertain about the path ahead when I first started out. Back then, I had no idea that the title “Machine Learning Engineer” even existed when I was working on my Text-to-Speech study for my Bachelor’s thesis. But it has become a popular and sought-after title, particularly among computer science students. With this in mind, I created a roadmap specifically for those interested in pursuing a career in this field. The roadmap starts with the basics and gradually builds up skills, one layer at a time. It’s worth noting that in today’s world and job market, having a Master’s degree is almost a requirement to land a job in this sector, as it can make a tremendous difference.It all starts with math. Linear Algebra, Statistics and Probability are our first requirements before jumping into ML algorithms. It’s important to have a strong foundation in these areas since Machine Learning is based on statistical and probabilistic models.
Books
Naked Statistics is a good book to start
Mathematics for Machine Learning
Videos
Khan Academy
MIT
2. Programming is the second skill set before jumping into ML algorithms. Machine learning involves a lot of mathematical and statistical concepts, so it’s essential to have a good understanding of data structures and algorithms.
Google has good libraries to develop your programming skills.
Cracking Coding Interview is a great book to develop your programming skills.
Intro to Python Course: it can be any language/course but Python is a well-known programming language to practice ML.
Develop a basic SQL understanding. An introductory video as follows: https://www.youtube.com/watch?v=h0nxCDiD-zg&ab_channel=KevinStratvert
You need to practice to be able to develop your programming skills so Hackerrank and Leetcode are great for this.
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