Portfolio

Introduction This is a project that I did as part of the Udacity scholarship and it entails using SageMaker for a complete project. AWS SageMaker provides a powerful environment for building, training, and deploying machine learning (ML) models at scale. This project demonstrates an end-to-end ML pipeline using AWS SageMaker, AWS Lambda, and AWS Step […]

Introduction Chatbots powered by large language models (LLMs) have transformed the way users interact with digital applications. By integrating LangChain, OpenAI’s GPT model, and Streamlit, developers can build an intelligent chatbot capable of retrieving information from PDF documents. This article explores how to set up and deploy such a chatbot using vector embeddings and similarity-based

Introduction In the era of big data, web scraping has become an essential skill for extracting valuable information from online sources. This article demonstrates a Python-based approach to web scraping using BeautifulSoup, data storage using SQLite, and data analysis using Pandas. The example focuses on extracting the top 50 highly ranked films from a webpage

Introduction Data analysis plays a crucial role in understanding economic and social trends across countries. This project utilizes R programming to analyze key global indicators such as Gross Domestic Product (GDP), unemployment rates, life expectancy, and the Global Reporting Initiative (GRI) scores. Using spatial visualizations, regression models, and correlation analysis, we investigate the relationships between

Project Overview The project involves creating a server that responds to client queries by searching through a text file. This system ensures efficient query handling and rapid response times, making it useful for applications requiring fast text searches. Installation Dependencies To install the necessary dependencies, use the following command: This ensures that all required Python

Introduction Bike-sharing systems have gained popularity in urban areas, necessitating accurate demand forecasting models. This project explores the use of AutoGluon to predict bike-sharing demand by leveraging automated machine learning (AutoML) techniques. The goal was to refine predictions through exploratory data analysis (EDA), feature engineering, and hyperparameter tuning. Initial Training Upon submitting initial predictions, it