Technical Toolkit
A practical technical stack for turning data into insights, predictive models, and deployable applications.
Expertise in Pandas, NumPy, and exploratory data analysis to uncover hidden trends.
Building end-to-end pipelines including feature engineering, classification, and model evaluation.
Developing neural networks and computer vision models using TensorFlow and Keras.
Creating interactive interfaces and apps for ML models using Streamlit and Joblib.
Proficient in Python, Java, Kotlin, and C, with a strong focus on clean, scalable code.
Crafting meaningful data stories with Tableau, Matplotlib, and Seaborn.
Completed a B.Tech in Computer Science and Engineering with a specialization in Data Science and Machine Learning at Lovely Professional University.
Built hands-on experience in Python, SQL, data preprocessing, exploratory data analysis, feature engineering, machine learning, deep learning, and model evaluation.
Applied data science and machine learning concepts to projects involving academic engagement, environmental data, computer vision, sports analytics, and predictive modeling.
Extended machine learning workflows beyond notebooks by building interactive applications and deployment-ready solutions using Python, Streamlit, and supporting ML tools.
Selected projects demonstrating practical experience across machine learning, deep learning, data analysis, and predictive modeling.
“Recognized among the top 10% of students in the Dean Category at Lovely Professional University.”
Dean Category — Top 10%
Academic Achievement at Lovely Professional University
“Advanced to Round 2 of the Adobe India Hackathon 2025.”
Adobe India Hackathon 2025
Hackathon Recognition at Adobe
GitHub Reposito
Featured Projects
Technologies Used
Research Project
Quick insights into my skills and career objectives.
I am open to new opportunities, collaborations, and technical discussions in Data Science and AI.
