Natural Language Toolkit with iPython Notebook and Python 2.7

Jupyter Notebooks consisting of various nlp tasks. (NLP role based interviews)

Natural Language Precessing related notebooks (Machine Learning)

compilation of notebooks

my notebooks using NLTK

Contains notebooks for NLTK, text analysis and NLP

Jupyter notebook, where I use nlp and practice regex

Online plagiarism checker scrapes the markdown text from submitted notebook link, searches the text on Google for possible matching notebook links on Jovian, Kaggle & Github sites, and returns the notebook links that contain the text.

Includes multiple notebooks, that covers different aspects of Natural Language Processing

I'll be uploading most of my machine learning practice notebooks here.

Machine translation is a popular topic in research with new papers coming out every year. Over the years of research, different methods were created, like rule-based, statistical, and example-based machine translation. With all this effort, it’s still an unsolved problem. However, neural networks have made a large leap forward in machine transla…

an iPython notebook using natural language toolkit to analyse President Obama's speeches

This notebook was created for the purpose of experimenting with natural language processing libraries and other tools, following tutorials online.

The ipython notebook is working to build a model which will detect duplicate questions if two questions pair are given.

This is a GitHub repository containing Jupyter notebooks and Python scripts related to natural language processing (NLP) concepts and techniques covered in the "NLP with Python" playlist by Codebasics YouTube channel. The notebooks cover topics such as text preprocessing, feature extraction using Python libraries NLTK, SpaCy

Repo to store code for #66DaysOfData challenge by Ken Jee. Includes notebooks and code for different concepts and technologies in data science for learning purposes.

This notebook contains entire text preprocessing pipeline for NLP problems. The ready-to-use functions require NLTK and SKlearn package installations. It also contains some prominent text classification models.