Hello, I'm

Param Chotaliya

AI/ML Engineer

Aspiring Data Scientist and AI/ML Engineer with a strong foundation in Python, machine learning, data analysis, and predictive modeling. Passionate about building intelligent, data-driven solutions to solve real-world problems while continuously learning and applying modern AI technologies.

Param Chotaliya

AI/ML Engineer

Python Logo Python
Pandas Logo Pandas
NumPy Logo NumPy
TensorFlow Logo TensorFlow
Scikit-Learn Logo Scikit-Learn

Skills

Technologies I Work With

Languages

Python Python l̥
HTML
CSS

Python Libraries

Scikit-learn Scikit-learn
Matplotlib
TensorFlow TensorFlow
NumPy NumPy
Pandas Pandas
Seaborn Seaborn
NLTK NLTK
Joblib Joblib
Pickle Pickle

Tools

Git
GitHub
AWS
VS Code
Jupyter Notebook
Streamlit
Supabase

Database / Container

MySQL
MongoDB
Docker

Projects

Models, Applications & Repositories

Restaurant Popularity Prediction

  • Engineered a predictive model utilizing Zomato's historical dataset (5000+ data points) to forecast restaurant popularity based on location, cuisine, and average cost.
  • Implemented a benchmarking feature that maps out local competitors and compares their customer ratings for strategic market analysis.
Python Scikit-learn Pandas Joblib Pickle Plotly

DeepFake Detection

  • Architected a multimodal deep learning system utilizing XceptionNet and AudioNet to detect sophisticated audio-visual deepfakes and media manipulations.
Python TensorFlow CNN NumPy

Midnight Chef (Leftover Food Recipe)

  • Built an AI-powered recipe recommendation web app that scans or manually logs ingredients and suggests dishes cookable now or with 1–2 missing items, using computer vision and a custom Rescue Scoring algorithm.
  • Implemented AI-driven recipe adaptation with Gemini Flash-Lite, backed by a nutrition engine trained on 3,000+ data points from IINDORI, USDA, and Food.com datasets.
  • Built a persistent saved-recipes system via Supabase with allergen filtering and preference storage.
CSS Python FastAPI Supabase

My Journey

Education

B.Tech - Computer Science & Engineering

GLS University
2023 - 2027

CGPA: 8.3

12th Grade (GSHSEB)

Shree Shubham School
2022 - 2023

Percentage : 74.30%

10th Grade (GSEB)

Shree Shubham School
2020 - 2021

Percentage : 93.5%

Achievements

Certifications & Extracurriculars

Certifications & Honors

  • AI Foundations - 7 Day Workshop

    Green Skill Initiative
  • 100% Merit Scholarship

    Secured a fully-funded merit seat (100% tuition waiver) at GLS University based on exceptional academic performance.

Extracurriculars & Hackathons

  • AI SaaS Hackathons

    Prototyped and delivered innovative technical projects at AI SaaS hackathons (CHARUSAT).

  • Adani Hack Innovate

    Competed in Adani Hack Innovate to rapidly build and pitch software solutions (Adani University).

  • Sports & Campus Events

    Participated in sports and events at GLS University.

Get In Touch

Contact Me

Contact now