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Achievement: Quickdraw

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Data-pageup/README.md

Name

Typing SVG

ABOUT ME

About Me

HOW I WORK

So, This is what I do every day & Night !


data
Collect
Gather data from multiple sources 		clean
Clean
Process & validate data 		explore
Explore
Analyze & visualize patterns 		engineer
Engineer
Create powerful features 		model
Model
Train & optimize algorithms 		evaluate
Evaluate
Test & validate performance 		deploy
Deploy
Ship to production 		monitor
Monitor
Track & improve

LET'S BUILD SOMETHING TOGETHER


Data Scientist • Data Analyst • ML Engineer

Building AI solutions | Exploring data insights | Deploying scalable models


Open for Collaboration & Opportunities




  



Available for full-time roles • | Open to research collaborations • | Ready to discuss ideas


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  1. EcoWaste-AI-Smart-Waste-Classification-Carbon-Footprint-Estimator EcoWaste-AI-Smart-Waste-Classification-Carbon-Footprint-Estimator Public

    EcoWaste AI uses MobileNetV2 to classify waste as organic or recyclable and a RandomForest model to estimate CO₂ savings based on item weight. It helps users make better disposal choices by providi…

    Jupyter Notebook 1

  2. YOLOv8_garbage_detection YOLOv8_garbage_detection Public

    A study comparing YOLOv8 Nano at 416×416 and 608×608 for garbage detection. It measures mAP, precision, recall, and speed, showing that higher resolution boosts accuracy while lower resolution runs…

  3. SmartFit_AI SmartFit_AI Public

    SmartFit AI uses machine learning to analyze fitness and health data, predict calorie burn, BMI, and body fat, and group users into fitness archetypes. It combines PCA, K-Means, and neural networks…

    Python

  4. RippleWorks RippleWorks Public

    A machine learning system that predicts Water Quality Index (WQI) and Water Quality Classification (WQC) using engineered water-quality features. The project includes full preprocessing with missin…

    Jupyter Notebook

  5. Hybrid_Generative_Adversarial_Neural_Network_and_Copula_DataSynthesizer Hybrid_Generative_Adversarial_Neural_Network_and_Copula_DataSynthesizer Public

    A Streamlit app that preprocesses your dataset and generates high-quality synthetic data using Gaussian Copula and CTGAN models, with built-in evaluation and easy CSV export.

    Python

  6. Energy-demanding-forecasting-using-ARIMA Energy-demanding-forecasting-using-ARIMA Public

    This project focuses on forecasting electrical load demand and solar power generation in Italy using ARIMA (AutoRegressive Integrated Moving Average) models. The analysis uses real-world time serie…

    Jupyter Notebook