df = pd.read_csv('aboutme.csv')
model.fit(X_train, y_train)
accuracy = 0.97
import Scikit-learn
print("Transforming data into decisions...")

Bhavya Mistry

data_scientist.analyze(['ML', 'Statistics', 'Deep Learning'])

About Me

Passionate about extracting meaningful insights from complex datasets and building predictive models that drive business decisions

📊

I'm a passionate 7th semester B.Tech IT student persuing career in Data Science, Machine Learning, and Artificail Intelligence. My journey began with curiosity about patterns in data and has evolved into building sophisticated models that uncover hidden insights and predict future trends.


15+
Projects

Experience & Education

Building expertise through experience and academic excellence

AI Intern

Bonrix Software Systems

Jul 2024 - Present

On-site

Python LLMs Database Flask API integration

Data Science Intern

Prodigy Infotech

May 2025 - May 2025

Online

Python Pandas Numpy Scikit-learn Matplotlib

B.Tech Information Technology

Indus University

2022 - 2026
CGPA : 9.78

HSC

A.G. High School and G. & D. Parikh Higher Secondary School

2022
Percentile Rank : 59.30

SSC

S.H. Kharawala Primary School

2020
Percentile Rank : 93.95

Skills

Comprehensive Skillset which I have acquired over time

Programmnig Languages

Python
SQL

Programming Tools

VS Code
Google Colab
Github
Postman

Machine Learning

Scikit-learn
XGBoost
TensorFlow (Exploring)
Neural Networks (Exploring)

Data Visualization

Pandas
Seaborn
Matplotlib
PowerBI

Database/ Backend

PostgreSQL
Flask
FastAPI

AI & NLP

NLTK
spaCy
Transformers
LangChain (Exploring)
Hugging Face (Exploring)

Featured Projects

Real-world applications of machine learning models with deployment and statistical analysis

🧑‍đŸ’ŧ

Customer Segmentation

A Customer Segmentation Tool built using KMeans clustering for classifying customers into segments based on their Recency, Frequency, and Monetary values (RFM)

541910 Customers Analyzed
4 Segments
KMeans Scikit-learn numpy pandas matplotlib pickle Streamlit
âœˆī¸

Flight Price Prediction

This project aims to predict the flight prices based on various features using machine learning models, including Linear Regression and Decision Tree Regression

73 R2 Score
Decision Tree Scikit-learn numpy pandas matplotlib pickle Streamlit
📃

Text Summerization

Build a basic model that summeries the given text using NLP

NLTK Regular Expressions
đŸŠē

Smart Health Predictor

This project uses the Diabetes Dataset and applies a Decision Tree Classifier to predict whether a patient has diabetes based on diagnostic measurements

80% Accuracy
8 Features
Decision Tree Logistic Regression Scikit-learn numpy pandas matplotlib
đŸšĸ

Titanic survival

A machine learning classification task aimed at predicting whether passengers survived the Titanic disaster based on various features such as age, gender, class, and other details

79.88% Accuracy
Decision Tree Scikit-learn numpy pandas matplotlib
đŸŒĨī¸

Single Image Dehazing

Project focused on removing haze from images by estimating the atmospheric light and transmission map using the Dark Channel Prior method to output a clear haze-free image

OpenCV Dark Channel Prior Guided Filtering matplotlib numpy
đŸĒģ

Iris Classification

This project uses ML model to predict the species of an iris flower based on its features

93% Accuracy
Decision Tree pandas matplotlib Scikit-learn Hyperparameter Tuning pickle Streamlit
đŸ’ŧ

Salary Predictor

This project makes use of ML model to predit the salary on the basis of years of experience

91% Accuracy
Linear Regression pandas matplotlib Scikit-learn pickle Streamlit

Certifications

Artificial Intelligence

Indus University

Getting Started with Machine Learning Algorithms

Simplilearn

Introduction to SQL

Simplilearn

Diploma in Multi-Lingual Computer Programming

C-DAC

Course on Computer Concepts

C-DAC

Get In Touch

Ready to collaborate on data science projects, research opportunities, or discuss the latest in AI/ML