Interview with Louis Owen

Louis Owen is the author of Hyperparameter Tuning with Python; we got the chance to sit down with him and find out more about his experience of writing with Packt.

Q: What are your specialist tech areas?
Louis: Artificial Intelligence, Machine Learning, Data Science, Natural Language Processing, Hyperparameter Tuning.

Q: How did you become an author for Packt? Tell us about your journey. What was your motivation for writing this book?
Louis: Before being reached out by Packt, I’d planned to write a book. However, writing a book is not only about writing the content. There is so much other necessary nitty-gritty stuff to be taken care of, and I still had too much on my plate. When the Packt team said they would handle all other things so I could focus on only writing the content, I thought this would be the chance I might never have again, so I said, “I’m in!”.

My motivation for writing this book was to provide a single source of truth for data scientists regarding the hyperparameter tuning concept. To the best of my knowledge, this is the first book that covers a wide range of hyperparameter tuning methods in a single book, not only about the theories but also the code implementation. It was also personal, as I wanted to prove to myself that I was able to do this.

Q: What kind of research did you do, and how long did you spend researching before beginning the book?
Louis: I spent a lot of time, hundreds or even thousands of hours, researching what content to be included in the book. Most done during writing the book with one goal, to ensure readers can get as much knowledge as possible from the book while presenting only the most relevant topics.

Q: What’s your take on the technologies discussed in the book? Where do you see these technologies heading in the future?
Louis: Data science is an evolving field. Hyperparameter tuning likewise. All of the hyperparameter tuning methods covered in this book are the top methods used by data scientists. However, it is super likely that, in the future, new SOTA methods will be introduced to the community. We need to keep our eyes open to the all future exciting updates, or maybe the second, third, or even Nth version of this book!

Q: Why should readers choose this book over others already on the market? How would you differentiate your book from its competition?
Louis: There are many great articles/books/courses already out there. However, to the best of my knowledge, there is still no single source of truth that covers a wide range of hyperparameter tuning methods, not only about the theories but also the code implementation. Readers will also be presented with a decision map that can help them to decide what method to be utilized for a specific condition they will face in practice.

Q: What are the key takeaways you want readers to come away with from the book?
Louis: That hyperparameter tuning is the ultimate step for improving the ML model’s performance. There are so many methods available out there, we may not need to know each of the methods, but we need to be able to decide which method to be used for our specific condition. Of course, you can utilize the decision map provided in this book to help you make the decision..

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

Q. How would you describe your author journey with Packt? Would you recommend Packt to aspiring authors?
An exciting journey where I’m able to learn a lot about the process of publishing a book. I definitely recommend Packt for other aspiring authors!

Q. What are your favorite tech journals? How do you keep yourself up to date on tech?
Mostly from LinkedIn, Medium, and tech community groups.

Q. How did you organize, plan, and prioritize your work and write the book?
I started by writing the name of each chapter along with the high-level description. Then, I started writing the headings of each chapter, followed by the key points to be included in each chapter. By doing this, I was able to keep the bigger picture in mind before jumbling my mind when writing the details of each heading in each chapter.

You can find Louis’s book on Amazon by following this link : Please click here

Hyperparameter Tuning with Python – Available on Amazon