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Comparing four different Deep Learning and machine Learning Algorithms to build a Spam Detector to identify unsolicited and unwanted emails. Exploring the process of classifying emails as spam or not spam by converting text data(emails) into vectors and Evaluate their performance
Review sentiment based on drug user reviews text/ dataset, using a supervised binary text classifier, which will classify user reviews as positive or negative
🤖💻This repository showcases a comprehensive Natural Language Processing (NLP) pipeline implemented in Python using Jupyter notebooks. The pipeline deploys various machine learning techniques to classify labeled dataset. The pipeline employs comparisons of the dataset using Recurrent Neural Network (RNN) and RandomForest Classifier algorithms.
📚🧠🌐 Welcome to TextAIHub repository! Explore the fascinating realm of NLP, text generation, sentiment analysis, and beyond. Join us in propelling language understanding to new frontiers through state-of-the-art AI models and advanced techniques. Together, let's ignite a revolution in text processing! 🚀💬🌍
Explore the world of text classification with this project that showcases a text classifier built from the ground up using a self-implemented Naive Bayes algorithm. Leveraging the 20 Newsgroups dataset from scikit-learn, this project guides you through the process of data exploration, preprocessing, and model training.