Harsh Garg
Passionate about machine learning and artificial intelligence.
Currently: B.Tech - Indraprastha Engineering College
✨ My Journey So Far
2020 – B.Tech - Indraprastha Engineering College
Pursuing a degree in Computer Science with a focus on user-centric design and AI applications.
2022 – Python for Data Science
Completed foundational training in Python tailored for data science workflows and analysis.
2023 – ML Model for Sales Prediction
Built an intuitive dashboard powered by a machine learning model to forecast retail sales.
2023 – Student Services Chatbot
Designed and developed a chatbot with a clean UI to simplify student access to campus services.
🧩 Proof of Work
SalesPredict: Machine Learning for Sales Forecasting
SalesPredict is a machine learning model developed to predict sales trends and forecast future sales based on historical data. Harsh built this model using Python and popular machine learning libraries such as scikit-learn and Pandas. The model analyzes sales data from past months, identifying patterns and trends, and then uses this information to predict future sales figures. Harsh utilized various machine learning algorithms including linear regression and decision trees to achieve high accuracy in predictions. The primary goal of the project I was to create a robust system that could provide businesses with data-driven insights to optimize inventory management, staffing, and marketing strategies. Harsh focused on data preprocessing to clean the dataset, handling missing values and scaling the features for improved model performance. The project also incorporated data visualization techniques to present the predicted sales data in a clear and interpretable format. The use of real-time sales data and predictive analytics allowed companies to make informed decisions, such as adjusting stock levels ahead of demand spikes or optimizing promotional strategies. This project helped Harsh gain hands-on experience with machine learning workflows, data preparation, and the implementation of predictive models. By leveraging machine learning for sales prediction, businesses can increase their operational efficiency and strategic decision-making.
Read more →CampusAssist: AI-Powered Chatbot for Students
CampusAssist is an AI-powered chatbot designed to assist students with campus-related queries, including information about courses, faculty, event schedules, and general campus facilities. Developed using Python, the chatbot leverages Natural Language Processing (NLP) techniques to understand and respond to user inquiries. Harsh integrated the chatbot with an easy-to-use user interface, allowing students to engage in real-time conversations through a simple chat interface. The system I was trained on various frequently asked questions and topics related to campus life, making it capable of providing instant and relevant responses. Harsh implemented NLP algorithms using libraries such as NLTK and spaCy to ensure that the chatbot can handle a wide range of student queries, from course-related inquiries to event updates. One of the key features of the chatbot is its ability to learn from interactions, adapting its responses to improve accuracy over time. This capability is achieved through machine learning models that continuously optimize the chatbot’s performance based on user feedback. Additionally, the chatbot can integrate with the campus information systems to fetch live data, such as course availability, event schedules, and faculty office hours. By providing immediate, automated assistance, the chatbot reduces the workload on campus administration and enhances the overall student experience. The project offered Harsh the opportunity to explore the application of artificial intelligence in real-world problem-solving, improving operational efficiency while providing students with timely information.
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