HomeAuthor InterviewsInterview with Dario Radečić on Machine Learning Automation with TPOT.

Interview with Dario Radečić on Machine Learning Automation with TPOT.

Q: What is/are your specialist tech area(s)?

Dario: Data science, machine learning, and programming in Python.

Q: How did you become an author for Packt? Tell us about your journey. What was your motivation for writing this book?

Dario: One of your Product Managers (Ali Abidi) contacted me and asked if I was interested in writing a book on automated machine learning. The idea interested me from the start, as I’ve written articles on this topic before.

Q: What kind of research did you do, and how long did you spend researching before beginning the book?

Dario: The research took a couple of weeks, at least before writing a single word. Further, each chapter required its dose of research. Lots and lots of research, put simply!

Q: Did you face any challenges during the writing process? How did you overcome them?

Dario: I would face challenges immediately if I tried to cut corners on research. Proper planning and extensive research were a way to go before writing a single word.

Q: What’s your take on the technologies discussed in the book? Where do you see these technologies heading in the future?

Dario: Data science and machine learning are still buzzwords, even in 2021. That effect will definitely fade over the years, more and more people will realize trying out and tuning a couple of algorithms isn’t a big deal, so it can be replaced with automation libraries such as TPOT. All of the activities leading to machine learning can’t be automated, on the other hand.

Q: Why should readers choose this book over others already on the market? How would you differentiate your book from its competition?

Dario: Put simply, this is the only “cover it all” book on TPOT. The reader doesn’t need to have extensive knowledge on machine learning. After reading 200 pages or so, the reader will know how to build automated models and also how to put them in production. Cramming that much information in less than 250 pages means no time is wasted on the non-essentials.

Q: What are the key takeaways you want readers to come away from the book with?

Dario: You don’t have to be a data scientist to benefit from data science and machine learning – there are automated libraries for that. Focus your time and efforts to data engineering – that field is much more difficult to automate.

Q: What advice would you give to readers learning tech? Do you have any top tips?

Dario: You’ll get frustrated a lot, but keep the effort consistent over the years. It’s the only way to do something remarkable.

Q: Do you have a blog that readers can follow?

Dario: Sure: https://www.betterdatascience.com

Q. Can you share any blogs, websites and forums to help readers gain a holistic view of the tech they are learning?

Dario: Just stay tuned to the ones provided in the last question.

Q. How would you describe you author journey with Packt? Would you recommend Packt to aspiring authors?

Dario: It has been a great journey, to say at least. Constant communication and just enough time to finish the drafts were the keys to success. Definitive recommendation to aspiring authors.

Q. What are your favorite tech journals? How do you keep yourself up to date on tech?

Dario: Medium.com mostly, I like the non-formal approach to complex topics.

Q. How did you organize, plan, and prioritize your work and write the book?

Dario: Weekly/daily planning and to-do lists. Book-wise, I split the work into main heading of the chapter, and then further split the tasks to code and writing. Finally, a good proofread and grammar check is a must.

Q. What is that one writing tip that you found most crucial and would like to share with aspiring authors?

Dario: Don’t waste people’s time. Boil everything down to essentials, even if it means to removing 90% of your piece.

You can find Dario’s books on Amazon by clicking on the cover image:

Machine Learning Automation with TPOT – Available on Amazon.com