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Data Science Intern
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Competencies
Utilized Python for machine learning modeling, data preprocessing, and analytics tasks.
Applied algorithms like SVM, Random Forest, and AdaBoost to build predictive models for water quality.
Handled data preprocessing, feature selection, and performance evaluation for model optimization.
Integrated IoT data streams into machine learning models for real-time water quality prediction.
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Summary
Focused on developing machine learning models and integrating IoT data for water quality analysis.
Key Achievements
- Developed a Water Quality Prediction System integrating SVM, IoT, and real-time data analytics
- Implemented data preprocessing, feature selection, model training & evaluation using multiple ML algorithms
- Contributed to end-to-end model development, focusing on data processing and performance optimization
Experience
Data Science Intern
Developing a Machine Learning–based Water Quality Prediction System integrating SVM, IoT and real-time data analytics to classify water potability., Implemented data preprocessing, feature selection, model training & evaluation using SVM, Random Forest, AdaBoost., Contributed to end-to-end...