Explore machine learning in Rust and learn about the intricacies of creating machine learning applications. This book begins by covering the important concepts of machine learning such as supervised, unsupervised, and reinforcement learning, and the basics of Rust. Further, you’ll dive into the more specific fields of machine learning, such as computer vision and natural language processing, and look at the Rust libraries that help create applications for those domains. We will also look at how to deploy these applications either on site or over the cloud.
After reading Practical Machine Learning with Rust, you will have a solid understanding of creating high computation libraries using Rust. Armed with the knowledge of this amazing language, you will be able to create applications that are more performant, memory safe, and less resource heavy.
Facebook's fastText library handles text representation and classification, used for Natural Language Processing (NLP). Most organizations have to deal with enormous amounts of text data on a daily basis, and efficient data insights requires powerful NLP tools like fastText.
This book is your ideal introduction to fastText. You will learn to create fastText models from the command line, without the need for complicated code. You will explore the algorithms that fastText is built on and how to use them for word representation and text classification.
Next, you will use fastText in conjunction with other popular libraries and frameworks such as Keras, TensorFlow and PyTorch.
Finally, you will deploy the fastText models to mobile. By the end of this book, you will have all the required knowledge to use fastText in your own applications at work or projects.
role: Team Lead - Machine Learning Platform
May 2017 → Current
As an individual contributor.
As a technical lead.
role: Category Head - Python
Nov 2016 → May 2017
role: Software Engineer
Aug 2015 → Oct 2016
role: Systems Engineer
Dec 2011 → Jul 2015