fastText is a lightweight Python library that was created to build scalable solutions for text representation and classification. It works on standard and generic hardware, smartphones, and small computers by utilizing functionalities that can reduce the memory consumed for fastText models. In recent years, fastText has been popular among the developer community as it is easy to use and is a reliable library for high-performance text classification purposes. This thorough guide to fastText covers why it’s so important.
What is fastText
fastText is an open-source library that Facebook AI developed in 2015. Its aim is to achieve scalable solutions for text classification tasks and process large datasets faster and more accurately. fastText can be used from a command line in Python or R with the fastText package. It is distributed under the BSD license, meaning there is a possibility to modify source codes and use them for private projects or use for commercial purposes. However, Facebook developers are not liable if someone has some faulty setup while using the codes in projects. fastText is helpful for developers, domain experts, and even students. It is dedicated to NLP tasks like text classification and learning word representations. fastText is designed to allow faster model iteration and refinement without the necessity of specialized hardware.
Moreover, you can train fastText models on more than a billion words on any multicore CPU within a matter of minutes. fastText also provides pre-trained models learned on Wikipedia and over 157 different languages. You can use fastText from the command line as well.
Download the ODSC Warmup Guide to fastText here
In this free-to-download guide to fastText, you’ll get everything you need to know to get started with fastText for NLP and machine learning! Just fill out the form below and get the guide emailed directly to you.
