Member-only story
Mastering NLP: In-Depth Python Coding for Deep Learning Models
A step-by-step guide with comprehensive code explanations for text classification using deep learning in Python
This article came to fruition after reading numerous documentation resources and looking at videos on YouTube about textual data, classification, recurrent neural networks, and other hot subjects on how to develop a machine-learning project using text data. A lot of the information is not that user-friendly and some of the parts are obfuscated, thus, I want to save the reader a lot of time and shed light on the most important concepts in using textual data in any machine learning project.
The supporting code for the examples presented here can be found at: https://github.com/Eligijus112/NLP-python
The topics covered in this article will be:
- Converting text to sequences
- Converting sequence indexes to embedded vectors
- In-depth RNN explanation
- The loss function for classification
- Full NLP pipeline using Pytorch
NLP stands for Natural Language Processing¹. This is a huge topic about how to use both hardware and software in tasks like:
