We are building a machine learning-based anomaly detection system using structured and sequential sensor data. The goal is to identify unusual patterns or faults through data modeling and visualization. This internship offers a real-world opportunity to work on machine learning pipelines and understand both supervised and unsupervised approaches to anomaly detection.This phase focuses on offline/static modeling using historical sensor data in tabular and time-series formats.🎯 Internship ObjectiveAnalyze sensor datasets representing various operational scenariosApply and evaluate supervised classification modelsTransition into unsupervised anomaly detection approachesVisualize insights and document findings for technical and non-technical audiences📘 Key ResponsibilitiesPerform data preprocessing: cleaning, encoding, normalization, and feature engineering

Train And Evaluate Classification Models Using

Artificial Neural Networks (ANN)Long Short-Term Memory (LSTM) models for sequence-based classification

Explore And Implement Unsupervised Anomaly Detection Techniques

Isolation ForestOne-Class SVMZ-score or IQR-based statistical methods

Analyze And Visualize Model Outputs Using

Confusion matricesAnomaly heatmapsTime-series plotsOptional: Build a lightweight dashboard (e.g., Streamlit) to present findingsAbout Company: TechnoExcel is the leading training and consulting company in Hyderabad offering data analytics solutions.

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Data Science Internship in Hyderabad (Hybrid)