What I learned from publishing 3 Technical Books on Machine Learning & Deep Learning

A brief guide for budding authors to effectively publish and scale

Over the past 4 years, I published 3 technical books on Machine Learning, Deep Learning and Decision Science, and the experience has been invaluable. Apart from new & better career opportunities, the process opened my doors to several other paths that I had never considered. In this post, I would like to summarize my key learnings and a few strategies that might help budding authors. I would like to walk you through the biggest pros and cons of publishing a book, what should one study before publishing, some good strategies to consider while publishing and finally a few strategies to adopt post publishing.

We will start with a brief history.

My story started off as a blogger. I started blogging in 2010 while I was a 3rd-year undergrad student. It was a blog that compiled study resources and course notes for Software Engineering students at Pune University. With the timing being about right and not much of competition for the blog, http://www.itportal.in/ garnered around 30K monthly visits during the time I was actively blogging. Later, in early 2013, I serendipitously got an opportunity to start my career in Data Science and the blogging…