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 Objective Analyze sensor datasets representing various operational scenarios Apply and evaluate supervised classification models Transition into unsupervised anomaly detection approaches Visualize insights and document findings for technical and non-technical audiences 📘 Key Responsibilities Perform 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 Forest One-Class SVM Z-score or IQR-based statistical methods Analyze And Visualize Model Outputs Using Confusion matrices Anomaly heatmaps Time-series plots Optional: Build a lightweight dashboard (e.g., Streamlit) to present findings About Company: TechnoExcel is the leading training and consulting company in Hyderabad offering data analytics solutions.

You will be involved in building a machine learning-based anomaly detection system using structured and sequential sensor data. Your main task will be to identify unusual patterns or faults through data modeling and visualization. This internship will provide you with a real-world opportunity to work on machine learning pipelines and understand both supervised and unsupervised approaches to anomaly detection. During this phase, you will focus on offline/static modeling using historical sensor data in tabular and time-series formats. Your primary objectives will include analyzing sensor datasets representing various operational scenarios, applying and evaluating supervised classification models, transitioning into unsupervised anomaly detection approaches, visualizing insights, and documenting findings for technical and non-technical audiences. Your key responsibilities will involve performing data preprocessing tasks such as cleaning, encoding, normalization, and feature engineering. Additionally, you will be required to train and evaluate classification models using Artificial Neural Networks (ANN) and Long Short-Term Memory (LSTM) models for sequence-based classification. You will also explore and implement unsupervised anomaly detection techniques like Isolation Forest, One-Class SVM, and Z-score or IQR-based statistical methods. Analyzing and visualizing model outputs using confusion matrices, anomaly heatmaps, and time-series plots will also be part of your responsibilities. Optionally, you may also be tasked with building a lightweight dashboard (e.g., using Streamlit) to present findings. TechnoExcel is the leading training and consulting company in Hyderabad offering data analytics solutions.,