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Hello! I’m Khushi Gajjar, a Data Science and Machine Learning enthusiast with a solid foundation in data preprocessing, ML algorithms, and statistical analysis. I love turning messy data into clear, data-driven insights and building end-to-end predictive models using Python, scikit-learn, and TensorFlow. I have hands-on experience with supervised and unsupervised learning, NLP, and data visualization through practical projects. I’m passionate about applying AI/ML to real-world problems and am excited to contribute to innovative AI solutions that empower smarter decisions.…Hello! I’m Khushi Gajjar, a Data Science and Machine Learning enthusiast with a solid foundation in data preprocessing, ML algorithms, and statistical analysis. I love turning messy data into clear, data-driven insights and building end-to-end predictive models using Python, scikit-learn, and TensorFlow. I have hands-on experience with supervised and unsupervised learning, NLP, and data visualization through practical projects. I’m passionate about applying AI/ML to real-world problems and am excited to contribute to innovative AI solutions that empower smarter decisions.

Khushi Gajjar

Data Analyst, AI Developer, Developer, +2

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Hello! I’m Khushi Gajjar, a Data Science and Machine Learning enthusiast with a solid foundation in data preprocessing, ML algorithms, and statistical analysis. I love turning messy data into clear, data-driven insights and building end-to-end predictive models using Python, scikit-learn, and TensorFlow. I have hands-on experience with supervised and unsupervised learning, NLP, and data visualization through practical projects. I’m passionate about applying AI/ML to real-world problems and am excited to contribute to innovative AI solutions that empower smarter decisions.…Hello! I’m Khushi Gajjar, a Data Science and Machine Learning enthusiast with a solid foundation in data preprocessing, ML algorithms, and statistical analysis. I love turning messy data into clear, data-driven insights and building end-to-end predictive models using Python, scikit-learn, and TensorFlow. I have hands-on experience with supervised and unsupervised learning, NLP, and data visualization through practical projects. I’m passionate about applying AI/ML to real-world problems and am excited to contribute to innovative AI solutions that empower smarter decisions.

Available to hire

Hello! I’m Khushi Gajjar, a Data Science and Machine Learning enthusiast with a solid foundation in data preprocessing, ML algorithms, and statistical analysis. I love turning messy data into clear, data-driven insights and building end-to-end predictive models using Python, scikit-learn, and TensorFlow.

I have hands-on experience with supervised and unsupervised learning, NLP, and data visualization through practical projects. I’m passionate about applying AI/ML to real-world problems and am excited to contribute to innovative AI solutions that empower smarter decisions.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Work Experience

Data Science & Machine Learning Intern at Param Group of Companies

May 1, 2025 - May 1, 2025

Cricket Score Prediction: Developed a machine learning model to predict cricket match scores using historical data and match context, enhancing forecasting accuracy and strategic analysis. Next Word Prediction Model: Built a transformer-based GPT model trained on textual datasets to generate contextually appropriate next-word predictions, showcasing understanding of NLP and deep learning architectures. Resume Screening App: Created an AI-powered resume screening application to automatically filter and rank resumes based on job descriptions using NLP techniques, streamlining the recruitment process.

Data Science & Machine Learning Intern at BrainyBeam Technologies Pvt. Ltd

June 1, 2024 - June 1, 2024

Collected, cleaned, and engineered features from a large dataset of car attributes (price, make, model, ratings) using pandas and NumPy; performed exploratory analysis with Matplotlib and Seaborn. Implemented collaborative and content-based filtering models using KNN and Random Forests for car recommendations based on user preferences and features. Applied precision, recall, F1-score, and RMSE to evaluate model performance; iterated through hyperparameter tuning for optimization. Deployed the recommendation system using Flask for real-time car suggestions, integrated with a web platform for scalability.

Cloud Computing Intern at Academor

July 1, 2023 - July 1, 2023

Worked with AWS and Azure platforms to create and manage scalable cloud solutions. Focused on cloud resource provisioning, automation, and performance tuning for cost-effective deployments. Developed a static website with a student records database and deployed it on Azure using Azure Storage Services. Optimized website performance, ensuring scalability and cost efficiency in cloud hosting.