Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.

The hands-on NLTK tutorial for NLP in Python

Python tutorials as Jupyter Notebooks for NLP, ML, AI

An introduction to Natural Language processing using NLTK with python.

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.

Jupyter Notebook for Natural Language Processing learning

This repository contains various models for text summarization tasks. Each model has a separate directory containing the implementation code, pretrained weights, and a Jupyter notebook for testing the model on sample input texts. Feel free to use these models for your own text summarization tasks or to experiment with them further.

Classifier that identifies Greek text as Cypriot Greek or Standard Modern Greek

NLP notebooks

Natural Language Toolkit with iPython Notebook and Python 2.7

Notebooks to tackle the Kaggle Spooky Author competition. The challenge is to accurately identify the author from their sentences.

Introducing Natural Language Processing (NLP) with jupyter notebooks.

A few Jupyter notebooks about Natural Language Processing

compilation of notebooks

Implementing text classification algorithms using the 20 newsgroups datasets, with python

This repo contains Report/Code/Notebooks of some of my projects

This repository contains the social media data scraper and the notebooks of this analysis. Where we analise the Social Media posts - tweets with Sentiment Analysis then we analyse this results with Named Entity Recognition (NER) and Information Extraction methods to get a more accurate and detailed picture of this sentiment results.

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.

Explore NLP tasks with Python using NLTK, SpaCy & scikit-learn: Tokenization, Normalization, NER, POS tagging, Encoding, Word embedding.

Estudo sobre análise e processamento de linguagem natural usando a biblioteca NLTK