Aspiring Gen AI Data Scientist | AI, ML & Deep Learning Enthusiast | EDA, Statistics & Excel | MySQL | Power BI | Python | Hadoop (Hive, Sqoop)
Welcome to my GitHub profile! I'm a passionate tech enthusiast exploring the fascinating world of data and programming. Here's a bit about me:
- 🎓 Fresher with expertise in Data Science and Data Analysis.
- 🔍 Actively seeking opportunities to create impactful solutions using data.
- 💡 Continuously learning and working on innovative projects to expand my skill set.
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Microsoft Malware Classification:
Built a robust classification pipeline to categorize malware into respective families using Microsoft's benchmark dataset. Performed feature extraction from large binary files and model optimization. Employed techniques like uni-gram byte feature extraction, with a strong focus on handling high-dimensional sparse data. -
Face Recognition Cricket Players Stats App:
Developed an innovative Streamlit-based application integrating OpenCV face recognition to detect cricket players from an uploaded image and display their stats. Combined image processing with sports analytics to build an interactive, user-friendly tool that merges computer vision with domain-specific data. -
Life Expectancy Prediction Model:
Built a Machine Learning model using Ensemble Learning techniques to predict Life Expectancy based on socio-economic and health-related factors. Applied Optuna-based hyperparameter tuning for performance optimization. Includes EDA, feature engineering, and model deployment via a Streamlit app. -
Employee Attrition Prediction:
Developed a classification model using Ensemble Learning techniques to predict employee attrition. Integrated Optuna-based hyperparameter tuning to improve model accuracy. Deployed an interactive Streamlit app for real-time predictions. -
UPI Transaction Data Analysis:
Interactive Power BI dashboard allows stakeholders to track and monitor monthly transaction volumes, payment methods, and city-wise distributions efficiently. -
Analyzing-Consumer-Trends-in-Protein-Supplements-Using-Exploratory-Data-Analysis:
Analyzed consumer trends in the protein supplement market using EDA techniques to help consumers make informed choices and assist businesses in optimizing their product strategies.
Feel free to explore my repositories and reach out for collaborations or discussions! 🚀