HomeAuthor InterviewsInterview With Author Dan Meador

Interview With Author Dan Meador

Dan Meador is the author of Building Data Science Solutions with Anaconda. 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 area(s)?

Dan: AI/ML, Python, Anaconda tools (conda, Navigator)

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

Dan: After thinking about writing for a while, I was actually approached about writing a Data Science book after joining Anaconda, but felt I was too busy learning about my new company. When Packt reached out again I thought it would be a challenge and opportunity I might never have again, so I said yes!

I wanted to create something that would give others a little bit of help along the way, and also create something that contained areas that I thought were gaps whenever data science is taught. 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?

Dan: There were hundreds of hours that were spent researching the book, and most was done during the process. I found that as I wrote chapters there were many things that would come up I never would have looked into, and also many things that I could have poured hours into only to never really need. This still happened some, but I tried to take a more iterative approach to writing rather than a waterfall look at the process.

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

Dan: There were many challenges that came along for me. One was learning how to be a new dad. The advice of “all they do is sleep” is something little Emily didn’t get the memo on. Even in her first few months, there were times that she would only take short naps during the day and slept like a baby at night … waking up all the time.

I also got Covid during the process, which was an all too common occurrence that many had to deal with. Fortunately I made a full recovery.

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

Dan: Data science is a mainstay tool that will only increase in its use in the future. The tools Anaconda makes will also prove to be the default way that creators and individuals will build the models that power our lives. The AI/ML field will be taught in every computer science degree across the county, and also be a core course in more business focused majors.

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

Dan: There are many great resources already out there, but for some reason there are critical areas that are never touched on. Bias and explainability are some. This book also digs into more detail the tools Anaconda gives you to get to the results you need. This level of detail into things like conda usage isn’t something you’ll find anywhere else. Lastly if you want to set yourself up for success, you need to understand how open source works, as its role is the only constant in the ever changing landscape.

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

Dan: – That AI/ML is ever changing, but there are tools that are staples which you can safely put time into mastering.
– You need to equip yourself with how to keep up and evaluate tools, as things will always be changing
– There are concepts that you can’t be ignorant about of think about only towards the end (or not at all) including bias and explainability.

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

Dan: Built something interesting to you! You will be hard pressed to really absorb concepts or ideas which you don’t see a use for. Create your own projects and always put them on GitHub so you can share and collaborate. There are also many open source projects that would love your help, no matter your skill level.

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

Dan: For many of the tools in the book, the official docs can be great resources. https://docs.conda.io/en/latest/ https://scikit-learn.org/stable/ Shameless plug, but Anaconda has a new website which is based around learning and community forums, with more features incoming: https://anaconda.cloud/ Some company blogs can have great articles on things they are doing, but I’ve found youtube to be incredible for learning. Some of the the better channels are: https://www.youtube.com/c/3blue1brown https://www.youtube.com/c/SirajRaval Andrew Ng is doing great work on teaching AI, just follow whatever he is doing.

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

Dan : A long journey. Packt was a great mix of helping keep me accountable while also understanding that I had other work and life events that come up and working with me on the schedule.

Q. Do you belong to any tech community groups?

Dan: I do go to some meetups and am in Slacks but nothing official.

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

Dan: Podcasts are great: Coding blocks .net (all things not just .net) , Talk Python to Me, Software Engineering Daily, and practical AI are all great.

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

Dan: I tried to really break it down into a focus per chapter, while keeping the bigger theme. I would write through the high level skeleton of the book, but also if inspiration would strike, dig into a section until I felt momentum was being lost, then pop back up to that higher level and keep going through at least the headers.

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

Dan: You probably know more than you think. Imposter syndrome is real, and I had to fight it along the way (and still do). There will no doubt be some mistakes that were made in the book, but I knew that I didn’t do it knowing it would be perfect.

All the quotes about “growth being hard” were what I was feeling during the process, and it wasn’t always comfortable, but In 50 years I’m not going to regret that I put myself out there.

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

Building Data Science Solutions with Anaconda Available on Amazon