My first book, Practical TensorFlow.js (Apress, 2020), is out!

As the name indicates, the book aims to teach TensorFlow.js through practical exercises, which cover algorithms ranging from traditional machine learning to deep learning, e.g., linear regression, k-means, convolutional neural networks, and generative adversarial networks.

Through hands-on examples, we apply these networks in use cases related to image classification, natural language processing, object detection, transfer learning, and time series analysis. The use cases include web applications, a game, making a Google Chrome extension, model deployment using Node.js, and more.

Now for the fun fact. I wrote the entirety of the book during my backpacking adventures from 2019-2020. The planning, outline, and first exercises were written and designed while I was in Japan and Singapore, and the rest in New Zealand. In the latter, I wrote while traveling the complete country, in places like hostels, libraries, camping sites, and a camper van; ah, and of course, during the unexpected Coronavirus lockdown time.

I sincerely want to thank everyone who helped me with the book. That includes my friends who corrected sections of it, those I was always bothering with stories about the book (sorry!), code reviewers, editors, technical editors, and Apress personnel.

These are some of the places you could find the book: