3 Tips to Build a Career in Machine Learning (Unconventional Advice)

Key Takeaways

pr3 somewhat unintuitive recommendations that will help you if you're trying to build a career in machine learning let's start right away with number one over the last two years I've gotten dozens of messages from software developers asking me how they can transition into machine learning sometimes they even ask how they can keep most of their salary when they transition into a more Junior position I want you to stop using words like transitioning or switching and start using words like Augmentin I want you to understand that the ultimate goal is to build software better software and machine learning happens to be a set of skills that will allow us to do that but machine learning is not the only ingredient that we need to build good software heck most of the time it's not even necessary it's not even the right answer if you're a software developer you spend years already building the skills that most companies need to design build and maintain good software that gives you a huge advantage and now you need to be adding to those skills not replacing so I want you to approach this new chapter in your career as an exercise of leveling up you are going to start building new skills new machine learning skills and start adding them up to the skills that you already have that's where the real power comes from so stop talking about Transitions and start talking about improvements before we talk about my second piece of advice I want to tell you that I've been a software engineer for the longest time in my career let me show you some this this here is my path everything I say and recommend it's based on my experience so here are the good news though despite of where you come from we are all going in the same direction and that's why I want you to consider this second piece of advice I want you to forget the code I'm focused 100 on the analysis this is what I mean analysis better than code the very first machine learning Professor that I paid attention to taught me this lesson he always said that he didn't care if we copied the entire solution of our homework I remember making the source code of my fourth assignment the solution that I wrote I made it available for my entire class my professor didn't care he always asked us to focus on the analysis of the problem our assignments were 100 focused on the why of the solution that we were choosing he didn't want to hear about the code he only cared about what was here and this advice has helped me over and over again because that's what machine learning is about it's about thinking and creativity and making decisions it's about ideas and frustrations and breakthroughs the code is the easiest part especially nowadays when we have access to so many tools and libraries and Frameworks that do all of the heavy lifting for us promise you you will rarely be stuck because you don't know how to code something instead you will mostly find yourself wondering what is the thing that you have to code in the first place before we get to the final piece of advice I want you to go to the comments below and type any questions you may have about starting with machine learning anything at all and I'm gonna try to record a video to answer the best comments I want you to break into the field and I think this is a great way of doing it so finally the third tip I have for you today third piece of advice recommendation however you want to call it many people will tell you to stay away from problems that are Classics problems that other people have solved over and over again I'm talking about the Titanic challenge the handwritten digit recognition the house pricing challenge Computing sentiment analysis for movie reviews all of those Classics now people claim you need to be original they question the value of solving a problem that 2 billion people have sold before and I would agree if you were building a portfolio to Showcase your skills but here we're talking about learning when you're studying you want to build your skill and there's nothing more effective than solving a problem that many other people have solved before and then having the opportunity to compare Your solution with them my brother poem my broader point is so so problems the beauty of machine learning is that there is never a single way to solve an exercise so if you work on a problem that you have access to many other Solutions you're gonna find hundreds of super smart and creative approaches that you could have used yourself and you will learn way more than if you are inside this black box trying to solve the problem by yourself so start solving problems from day one and right now I want you to take a look at this video here for an introduction to a tool you'll need the very first day you build a classification machine learning model and I'll see you in the next one