Get to know me
I’m a naturally curious person who enjoys exploring how things work, and that curiosity is what drives me toward becoming a Data Scientist. Over time, I’ve built strong skills in Python, Data Analysis, and Machine Learning, and I’ve had the chance to apply them through several real projects during my studies. Working on these projects has helped me understand data more deeply, uncover meaningful insights, and create solutions that actually solve problems. I genuinely enjoy turning raw data into something useful and building models that make sense of real-world situations. I keep learning and improving every day, and I’m committed to growing into one of the top Data Scientists in the field.
my intro
I am a student and an aspiring Data Scientist from India with growing experience in Python, Data Analysis, and Machine Learning. I’ve worked on several projects that involve cleaning data, finding insights, and building practical models. I enjoy solving real problems with code and turning information into something meaningful. I stay curious, learn fast, and constantly work on improving my skills to deliver better results every day.
My level of knowledge in some tools & tech stack
Special Things About Me
I can develop predictive models, analyze complex datasets, and deliver customized dashboards and insights aligned with your project needs.
Creating interactive dashboards and visual reports to transform raw data into meaningful business insights.
Designing, managing, and querying relational databases to store, organize, and extract structured data efficiently.
Building high-performance automation, data pipelines, and analytical solutions using advanced Python concepts and libraries.
Implementing efficient data handling methods and problem-solving techniques to optimize computation and performance.
Developing predictive models that learn from data to solve classification, regression, and real-world business problems.
Creating neural-network-based systems for tasks like image processing, NLP, and advanced pattern recognition.
Analyzing large-scale datasets using modern tools to uncover hidden trends, patterns, and valuable insights.
Deploying and managing scalable applications and data solutions using cloud platforms for high performance and flexibility.
My Academic Background
School Name : Ankur Vidhya Vihar
Course : 11–12 Commerce
Batch Year : 2021–2023
Percentage : 85%
City : Surat, Gujarat
College Name : Natubhai V. Patel Pure Applied Science
Course : BSc AI & ML
Batch Year : 2023–2026
CGPA : 8.91
City : Anand, Gujarat
Company : Venom Technologies
Duration : 05/12/2025 to 01/01/2026
Location : Anand, Gujarat
Working as a Data Science Intern at Venom Technologies was one of the most valuable learning experiences of my journey in AI and Machine Learning. During the internship, I had the opportunity to work with real-world datasets, understand how data is used in actual business environments, and transform raw information into meaningful insights through analysis and visualization. From performing data cleaning and exploratory analysis to building machine learning models and identifying patterns, every task helped me strengthen my technical skills while also improving my problem-solving approach. What made this experience truly special was the supportive environment and the chance to learn how data-driven decisions can create real business impact. The internship not only enhanced my practical knowledge of Data Science but also increased my confidence in working on real industry-level projects.
This are my strongest sides
Python Libraries Mastered
Extensive Dataset Analysis Done
End-to-End Data Projects Completed
Tools & Technologies Learned
Showcasing some of my best work
I developed an end-to-end AI-powered Stock Price Forecasting System using Python, TensorFlow/Keras, Flask, and Yahoo Finance API to analyze and predict next-day stock market trends from real-time financial data. The project involved collecting and preprocessing 10+ years of historical stock data, performing feature engineering on OHLC values and technical indicators, and building deep learning models for time-series forecasting. I implemented automated prediction pipelines, model evaluation using R² Score, RMSE, and MAE, and optimized performance through hyperparameter tuning, dropout , regularization, and early stopping techniques. To make the system scalable and user-friendly, I built a Flask-based web application capable of dynamically forecasting multiple stock tickers while visualizing actual vs predicted trends through interactive analytical dashboards.
I completed a comprehensive Telecom Sector Data Analysis project using real operational data provided directly by the organization. The project involved performing in-depth data cleaning, exploratory data analysis, customer behavior insights, churn pattern evaluation, and identifying key performance drivers within the telecom dataset. Building on these insights, I developed a machine learning model to predict important business outcomes, enabling data-driven decision-making. This project reflects my ability to work with real industry data, derive meaningful insights, and build predictive models that support strategic improvements in the telecom domain.
I built a Laptop Price Prediction project using a real-world open-source dataset to demonstrate my complete data science workflow. The project covers data preprocessing, exploratory data analysis, feature engineering, and building a reliable machine learning model to estimate laptop prices based on their specifications. To enhance accessibility, I deployed the model through an interactive Streamlit web application, enabling users to input features and instantly view predictions. Additionally, I containerized the entire application using Docker and published it on DockerHub, making it easy to run and deploy across different environments. This project highlights my ability to take a machine learning solution from development to production-ready deployment.
I developed an Insurance Prediction project to strengthen my understanding of API development and machine learning deployment. Using a custom JSON dataset of 20 patient records, I performed data preprocessing and built a predictive model to estimate insurance charges based on key health-related features. To explore backend development, I created a fully functional FastAPI endpoint that serves real-time predictions through a clean and scalable API. I also built an interactive Streamlit interface where users can input patient details and instantly receive predicted insurance costs. This project demonstrates my ability to design datasets, build machine learning models, develop APIs, and integrate them into user-friendly applications
I conducted an in-depth IPL Data Analysis project to explore performance patterns, team strategies, and player statistics across multiple seasons. The project involved extensive data cleaning, exploratory data analysis, visualization, and identifying key insights such as top-performing players, match-winning factors, batting/bowling trends, and team comparisons. Through meaningful charts and metrics, I transformed raw IPL data into actionable insights that highlight how various factors influence match outcomes. This project showcases my ability to analyze large sports datasets and communicate insights through clear, data-driven storytelling
I developed an interactive Power BI Dashboard for an e-commerce dataset to showcase advanced business intelligence and reporting skills. The project involved performing data cleaning, data modeling, and creating DAX measures to derive meaningful KPIs such as sales performance, customer behavior, product profitability, and order trends. Using dynamic visuals, slicers, and drill-through features, the dashboard provides a clear, data-driven view of overall business performance and helps identify actionable insights. This project highlights my ability to transform raw data into intuitive, decision-ready visual analytics using Power BI and DAX.
I developed a full stack e-commerce website for Rivaayat Jewels, an imitation jewelry brand, using modern frontend and backend technologies. The project includes a responsive product catalog, category-wise product listing, user-friendly shopping interface, authentication system, cart functionality, and order management features. I designed the frontend with a clean luxury-inspired UI and connected it with backend logic to store customer details, product data, and order information securely. This project reflects my ability to build real-world business websites with frontend design, backend development, database integration, and scalable e-commerce functionality.
I developed a fully responsive Frontend Travel Booking Website designed to provide users with a smooth and attractive booking experience. Using modern web technologies such as HTML, CSS, JavaScript, and clean UI components, the site includes sections for destination exploration, booking forms, travel packages, and user interaction elements. The layout is optimized for both desktop and mobile, ensuring an intuitive, visually appealing browsing experience. This project highlights my front-end development skills, UI/UX understanding, and ability to build polished, user-friendly web interfaces.
Feel free to contact me anytime
Seeking challenging opportunities in data science to apply my technical and analytical abilities and gain valuable experience. Open to professional engagements