This is my portfolio of Natural Language Processing projects. Each project includes a brief overview, the tools and technologies used, and the outcomes achieved. All of the code and relevant datasets are available in the corresponding project repository.

• Project 1 : BBC Headlines Classifier using RNNs
• Project 2 : Instagram Poet using OCR and RNNs

In this project, I built a Recurrent Neural Network (RNNs) to perform Multi-Label Classification on the BBC Headlines Dataset using Tensorflow and NLTK libraries for both preprocessing, and model building, training and validation respectively

Key Tech: Recurrent Neural Networks (RNNs), Multi-Label classification, NLTK & Tensorflow

In this project, I performed Webscraping to obtain a random instagram poet's posts, then performed Object Character Recognization (OCR) to strip the texts from the posts and then built and trained a Recurrent Neural Network (RNNs) to generate poetry from a given seed word.

Key Tech: Webscraping , Object Character Recognization (OCR), RNNs, Text Generation & Tensorflow

The NLP projects in this portfolio use the following dependencies:

• Python 3.x
• Natural Language Toolkit (NLTK)
• Scikit-learn
• Pandas
• Numpy
• Tensorflow
• Keras
• Matplotlib

You can install these dependencies using pip.

pip install tensorflow nltk scikit-learn numpy matplotlib 

Each project is contained in its own directory, and includes a README file with detailed instructions on how to run the project and use its functionalities.

This NLP portfolio showcases my expertise in various NLP techniques, such as text classification, sentiment analysis, topic modeling, and text generation. Each project is designed to address a specific NLP problem and includes a detailed description of the problem statement, data analysis, model selection, and evaluation. The portfolio includes projects using both traditional machine learning techniques and deep learning models, providing a comprehensive view of my NLP skills.