This project is a powerful application that leverages the capabilities of Language Models (LLMs) and generative AI to provide intelligent responses to questions related to PDF documents.
This project focuses on applying unsupervised learning techniques to perform customer segmentation, a vital task in understanding and targeting different customer groups based on their behavior, preferences, and characteristics. By leveraging machine learning algorithms, this project enables businesses to gain valuable insights into their customer base and tailor their marketing strategies accordingly.
This project is a powerful web scraping application that utilizes the Python libraries Selenium and Beautiful Soup to extract product information and data from the Amazon website. By automating the browsing process and parsing the HTML content, this application enables users to gather valuable insights and data from Amazon's extensive product catalog.
This project revolves around building a movie recommendation system that leverages the power of Python and collaborative filtering techniques to provide personalized movie recommendations to users. By analyzing user preferences and similarities among movies, this system helps users discover new movies tailored to their tastes and interests.