Here are some of the key projects related to Natural Language Processing (NLP) and Deep Learning that we have been working on:
Sentiment Analysis 🎯: We have developed a deep learning model to analyze the sentiment of text data. This project uses pre-trained language models like BERT and fine-tunes them on specific datasets.
Text Classification 📊: Our team has created a classifier that can categorize text into predefined categories such as sports, finance, technology, etc. This is achieved through convolutional neural networks (CNNs) and recurrent neural networks (RNNs).
Machine Translation 🌍: We are currently working on a deep learning-based machine translation system that can convert text from one language to another with high accuracy.
Named Entity Recognition (NER) 🏢: This project involves identifying and classifying named entities in text such as persons, organizations, locations, and expressions of times. We are using a combination of CNNs and attention mechanisms for this task.
Summarization 📝: Our goal is to create a model that can automatically generate summaries of long texts. We are exploring different techniques, including extractive summarization and abstractive summarization.
For more information about our projects, check out our project repository.