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Interview with Mark Ryan

Mark Ryan is the author of Deep Learning with Fastai Cookbook, we got the chance to sit down with him and find out more about his experience of writing with Packt.

Q: How did you become an author for Packt? Tell us about your journey?

Mark: Packt approached me with the idea of writing a book about fastai and I was intrigued. I really enjoyed Howard and Gugger’s book on fastai, but I thought there was room for a book that focused on the bread and butter coding recipes needed to get started with fastai.

Q: How long did it take you to write the book?

Mark: 10 months

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

Mark: I needed to review forums and other material about fastai and create many code examples. I spent several months researching before I began writing and then continued researching while I was writing.

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

Mark: Yes. The main cloud environment that I used for development, Paperspace Gradient, went through a major upgrade while I was developing the code for the book, and some things stopped working. Fortunately, I was able to engage Paperspace support about the problems and they were very responsive. Now the platform is extremely stable.

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

Mark: Start applying what you are trying to learn right away. Have a couple of side projects on the go and keep trying to exercise what you have learned in the side projects.

Q. How do you keep up-to-date on your tech?

Mark: I follow several blogs and, especially, listen to podcasts or technical YouTube videos while I am exercising or commuting. That way I get a high-level idea of what is happening. When something looks particularly interesting, I can dig into it with a coding exercise.

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

Mark: https://markryan-69718.medium.com/

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

Mark: • To dig deeper into fastai, you can check out the online documentation for the framework (https://docs.fast.ai/).
• If you want the comprehensive guide to fastai, I highly recommend the outstanding book from Jeremy Howard (the originator of fastai) and Sylvain Gugger: Deep Learning for Coders with Fastai and PyTorch (https://www.amazon.com/Deep-Learning-Coders-fastai-PyTorch/dp/1492045527).
• Jeremy Howard’s YouTube channel (https://www.youtube.com/user/howardjeremyp) is another excellent source of information about fastai, including videos of Howard’s deep learning course built on fastai.
• When you are ready to go even deeper, Zachary Mueller’s Walk with fastai site (https://walkwithfastai.com/) is a fantastic resource that consolidates many insights from the fastai forum (https://forums.fast.ai/) along with Mueller’s own encyclopedic understanding of the platform.

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

Mark: It was challenging and fast-paced, but I felt like my time was being used well. The Packt approach is not easy for a first-time author, but I think that an author who has already written one book will appreciate the straightforward way that Packt organises the projects and, especially, the simplicity of the authoring templates.

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

Deep Learning with Fastai Cookbook is Available on Amazon.com