UpFlairs (Data Science with Machine Learning & AI)During my internship at UpFlairs, I engaged in multiple projects focusing on Machine Learning (ML) and Artificial Intelligence (AI), applying advanced data science concepts to real-world scenarios. My responsibilities included data analysis, model development, deployment, and cross-functional collaboration.Major Duties:Developed, trained, and optimized machine learning models.Conducted data preprocessing, feature engineering, and visualization.Integrated AI-driven solutions into web applications using Flask and Streamlit.Key Achievements:Customer Satisfaction Prediction: Built a logistic regression model to predict customer satisfaction from feedback data, achieving 90% accuracy. Deployed the model using Flask for web-based predictions.Email Classification: Created a machine learning model to classify emails as spam or ham, leveraging natural language processing techniques and deploying it in a web application.Image-Driven Chatbot: Worked on a chatbot that combined image and text inputs to generate human-like responses using Deep Learning and NLP. Integrated Google Generative AI and Gemini API, with a Streamlit frontend for interaction.Insurance Price Prediction: Predicted insurance costs using regression techniques, optimizing the model's accuracy for commercial use.Highlighted Project:Customer Satisfaction Prediction: Analyzed customer feedback data, developed a logistic regression model, and deployed it in a Flask-based web app. This project provided real-time sentiment analysis for businesses, highlighting my skills in end-to-end machine learning workflows.This internship honed my expertise in AI, ML, and NLP, enabling me to deliver impactful, AI-driven solutions to real-world challenges.

During my summer internship at Learn and Build in Jaipur, I gained extensive hands-on experience in data science and machine learning. I worked on real-world projects that involved data cleaning, transformation, and visualization using Python libraries such as Pandas and NumPy. I implemented and fine-tuned machine learning models, including regression, classification, and clustering algorithms, achieving significant accuracy improvements. Additionally, I led a project to develop a predictive model for customer churn, collaborated with cross-functional teams, and presented findings to stakeholders. This internship provided me with a solid foundation in data science techniques, machine learning algorithms, and the practical application of these skills to solve complex problems.

Exhibitedeffectiveprojectmanagementskillsbyoverseeingtheentiredevelopment lifecycle,ensuringsuccessfulexecutionanddeliveryoftheIoT-basedHomeAutomation project.LedthedesignanddevelopmentofaninnovativeIoT-basedHomeAutomationsystem atPIETAICTEIDEALABinJaipur,integratingsensors,amicrocontroller,andsmartlights topersonalizehomeequipmentautomation.