Hands-On Machine Learning with TensorFlow.js30 Nov 2019
Now, I have got a chance to write a book about the hands-on guide of machine learning models using TensorFlow.js from Packt, named Hands-On Machine Learning with TensorFlow.js. It has been published the other day.
That is a practical guide to build the various kinds of machine learning applications on the web platform. It covers several use cases, which is common in real-world machine learning applications. Here is the table of contents of the book.
- Section 1: The Rationale of Machine Learning and the Usage of TensorFlow.js
- Machine Learning for the Web
- Importing Pretrained Models into TensorFlow.js
- TensorFlow.js Ecosystem
- Section 2: Real-World Applications of TensorFlow.js
- Polynomial Regression
- Classification with Logistic Regression
- Unsupervised Learning
- Sequential Data Analysis
- Dimensionality Reduction
- Solving the Markov Decision Process
- Section 3: Productionizing Machine Learning Applications with TensorFlow.js
- Deploying Machine Learning Applications
- Tuning Applications to Achieve High Performance
- Future Work Around TensorFlow.js
Notably, section 2 should be useful for developers who are eager to learn how to write an application with TensorFlow.js practically. I have introduced several machine learning algorithms written with TensorFlow.js alongside showing the examples to solve simple problems. Readers will get used to the useful APIs and practical manner of how to use them.
Additionally, Packt writes a blog article illustrating the highlight of the book based on my interview. It gives us an excellent overview and motivation behind the book.
- TensorFlow.js contributor Kai Sasaki on how TensorFlow.js eases web-based machine learning application development
I would be so glad if you are developers in the machine learning field and interested in applying the machine learning application in the web platform by using TensorFlow.js. The book will be an excellent start.
Last but not least, Packt gave me a chance to write the book to add new practical material for TensorFlow.js on the shelf. The writing was not easy for me, but I was able to obtain valuable experience as a software engineer working in the field. Thank you so much!