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Creating Beautiful Experiences
I am Jatin Kushwaha, a pre-final year Integrated M.Tech. (CSE) student in Computational and Data Science at VIT Bhopal. Passionate about Machine Learning, Data Analytics, and Web Development, I have worked on projects like Brain Tumor Detection and Fresh vs Rotten Fruit Classification. Skilled in Python, ML/DL, Data Visualization, and Full-Stack Development, I aim to contribute as a Data Science Intern and Web Developer by solving real-world challenges.
November 2024 – January 2025
Prodigy InfoTech
Remote
Executed EDA, data preprocessing, feature selection, sentiment analysis, geospatial analysis, and data visualization using Python, Pandas, Seaborn, Matplotlib, Scikit-learn, and NLP techniques.
Built a Decision Tree Classifier with over 89% accuracy and extracted actionable insights from Titanic and accident datasets using clustering, dimensionality reduction, and feature engineering visualizations.
September 2024 – November 2024
Quintus Tech Pvt.Ltd
Indore
Built and optimized a full-stack e-commerce website using HTML, CSS, JavaScript, React, and RESTful APIs. Implemented secure login/signup authentication and dynamic product management features.
Improved application performance, user experience, system reliability, and scalability by integrating third-party APIs and designing a robust modular backend and architecture.
2024 – 2025
CodeClause Pvt. Ltd
403, Lane A-5, Nivrutti Nagar Vadgaon Bk-411041 Pune, India.
Developed and deployed machine learning models for real-world datasets, focusing on classification and prediction tasks.Applied data preprocessing, feature engineering, and visualization techniques to derive actionable insights.
Enhanced problem-solving skills by implementing Python-based solutions for analytics use cases. Collaborated in an educational internship program to strengthen expertise in Data Science and Software Development.
Built a binary classifier using 3,000 MRI images, applying preprocessing (noise reduction, normalization, augmentation) and evaluating seven ML models in brain tumor detection as Tumor or No Tumor. Extracted texture, shape, and intensity features using GLCM and histograms, achieving 96% accuracy withLogistic Regression and Random Forest, evaluated via F1-score, AUC, and confusion matrix. Built ML framework for brain MRI analysis using image transformations and features for reliable diagnosis.
Developed a Sequential CNN-based model to classify apples, bananas, and oranges as fresh or rotten using a Kaggle dataset (13.5k images). Achieved 98.79% accuracy, with strong precision and recall scores. Applied preprocessing,augmentation,and dropout techniques to enhance model robustness,prevent overfitting. Explored transfer learning to achieve scalable performance with real world use in agricultural quality control.
Developed a conversational Generative AI-powered assistant for e-commerce that integrates Large Language Models (LLMs) with a structured database. The agent can process user queries in natural language, execute SQL queries dynamically, and return insights such as sales analytics, customer eligibility, and product performance. The solution also features a web-based interface with interactive UI for seamless user interaction.
Developed a simple linear regression model to predict house prices based on features such as the number of bedrooms and square footage. The project involved data preprocessing, model training, and evaluation, achieving an accuracy of ~85% in predicting house prices.
Designed and developed an interactive Spotify Data Analytics Dashboard to analyze global music streaming trends. The dashboard provides insights into the most popular tracks and artists, country-wise streaming distribution, streams over time, and yearly positions. It enables users to visualize streaming patterns and identify top-performing songs and artists across different regions.
2021
Vellore institute of technology ,Bhopal
GPA: 8.52
2021
Holy Angels Higher Sec.School
GPA: 88.6%
2019
Angels Public High School
GPA: 85.4%
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