fastText Quick Start Guide

Contents

1: INTRODUCING FASTTEXT

2: CREATING MODELS USING FASTTEXT COMMAND LINE

3: WORD REPRESENTATIONS IN FASTTEXT

4: SENTENCE CLASSIFICATION IN FASTTEXT

5: FASTTEXT IN PYTHON

6: MACHINE LEARNING AND DEEP LEARNING MODELS

7: DEPLOYING MODELS TO WEB AND MOBILE

What You Will Learn

Create models using the default command line options in fastText
Understand the algorithms used in fastText to create word vectors
Combine command line text transformation capabilities and the fastText library to implement a training,validation,and prediction pipeline
Explore word representation and sentence classification using fastText
Use Gensim and spaCy to load the vectors,transform,lemmatize,and perform other NLP tasks efficiently
Develop a fastText NLP classifier using popular frameworks,such as Keras,Tensorflow,and PyTorch

Authors

Joydeep Bhattacharjee

Joydeep Bhattacharjee is a Principal Engineer who works for Nineleaps Technology Solutions. After graduating from National Institute of Technology at Silchar,he started working in the software industry,where he stumbled upon Python. Through Python,he stumbled upon machine learning. Now he primarily develops intelligent systems that can parse and process data to solve challenging problems at work. He believes in sharing knowledge and loves mentoring in machine learning. He also maintains a machine learning blog on Medium.
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