How to Successfully Pursue a Career in Machine Learning - Blaine Bateman
Blaine Bateman is the co-author of The Supervised Learning Workshop. In our recent interview we got a chance to learn more about him, his thoughts on Machine Learning & AI and his recent workshop with Packt.
1. Can you tell us about your career and how you got to where you are today?
I began my career in Chemical Engineering in 1982. During the first part of my work, I was in research labs and did a lot of computer coding as well. I began consulting with my own company in 2011 and saw a huge need for better analytics. That led me to machine learning, which is my complete focus now. Along the way, I worked in biotech, cryogenics, instrumentation, computer storage, antenna design, and electronics.
2. Anything you’d do differently?
I would tell my younger self to talk less, listen more, and make learning an integral part of your life. Now I learn constantly, and it is very rewarding.
3. What are your biggest achievements?
During my work for the Federal Government, I was awarded the US Department of Commerce Bronze Medal. I’m also proud of one of my antenna patents because the design is so interesting from the electromagnetics point of view.
4. What is your chosen technology area and why it is so interesting?
I focus on Machine Learning and Predictive Analytics. I love this area because it is still relatively new, so there are lots of discoveries and advancements happening all the time. It’s also close to the Open-Source Software movement which is very exciting as it gives us most of the tools we use. Given that we are increasingly a data society, I see ML and related areas as having a long life.
5. What is your view on bias in machine learning?
I am concerned about bias in machine learning models for a lot of reasons, but I don’t think it is insurmountable or a reason to stop pursuing ML.
I think part of the challenge starts with the hype and excitement around machine learning (and artificial intelligence) which led companies to apply ML before thinking about all the consequences. Some applications I’ve seen are obviously at high risk to produce biased results, and we need to educate managers to think about that. Another problem which can create bias is the lack of diversity in the field. For my part, I really encourage women to get involved with ML (and science & technology in general) because we need as many different viewpoints as possible.
6. You’ve created a workshop with us, what is it about and who benefits from it?
The Supervised Learning Workshop teaches readers about a large part of Machine Learning, which is building and training predictive models using data where we know the “answers” for the data we have. A great aspect of the workshop is that it is accessible to a lot of levels of learners. If you have a bit of Python coding skills, you can use this workshop to jump start into the field of Machine Learning. There isn’t too much theory or math in the workshop; it is intended to be hands on and practical.
7. What jobs or career doors this workshop will open?
Anyone with an interest in becoming a Data Analyst or Machine Learning Practitioner would find this workshop an excellent starting point. The methods taught in the workshop could help junior analysts increase their skill and value to their companies for professional advancement and growth.
8. How will this workshop help someone become better at what they do at work on daily basis?
I think this workshop is good for someone who might be working in coding and interested in changing or enhancing their career. Also, business analysts who might mainly work with proprietary platforms in enterprises today can use this workshop to begin applying their own code and models to analysis problems already at hand.
9. What advice would you have for someone who wants to become a Machine Learning Practitioner?
Machine Learning is a big field with many exciting applications, and that means there is a lot to learn. You can use a workshop like this as a starting point to see if this really interests you and to learn some good foundational methods.
You must keep learning, though! Make it a practice to read in the field very often and try projects on your own. If you find an area you are weak in or just uncomfortable, take advantage of the array of online resources to fill in your learning. Treat every new project as an opportunity to apply something new or improve your skills, instead of as just a job to finish.
10. Where can we find the workshop?
The Supervised Learning Workshop can be found at Packt, and all the regular book retailers like Amazon and such as well.
