1. A powerful, modular recommendation engine that delivers personalized content, product, or user suggestions using collaborative filtering and content-based techniques.
2. An advanced AI-driven image generation tool that transforms user prompts into stunningly realistic, high-quality visuals using the powerful FLUX model from Hugging Face.
3. (a) A Sentiment Analysis tool built using Python and NLTK (Natural Language Toolkit). It processes text data, classifies sentiment as Positive, Negative, or Neutral, and provides insights into the overall mood of the dataset.
(b) This project also demonstrates how to build a state-of-the-art sentiment analysis model using the Hugging Face Transformers library. Instead of training from scratch, it leverages pretrained transformer models (like BERT, DistilBERT, or RoBERTa) and the simple pipeline API to classify text into Positive, Negative, or Neutral sentiments.
(c) And then at the end the best one- Using Pipelines and transformers