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-											   Empowering Sentiment Analysis: Text Classification of Airline Tweets
+											   AI-Powered SLAM for Autonomous Navigation
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 									<a href="https://github.com/sri-dsa/blob/main/machine_learning/NLP_supervised.ipynb" class="image fit"><img src="images/air.jpeg" alt="" /></a>
-									<p>Embark on an empowering exploration as we harness the potential of text classification using the "airline_tweets" dataset. Through sentiment analysis, we aim to classify the tweets and gain valuable insights into customer emotions, opinions, and experiences with airlines. Get ready to interactively navigate through the world of textual data and uncover the true sentiment behind each tweet, empowering businesses to make data-driven decisions for improved customer satisfaction.</p>
+									<p>This project implements Simultaneous Localization and Mapping (SLAM) to enable autonomous robots to navigate unfamiliar environments. Using LiDAR, Visual SLAM (ORB-SLAM, RTAB-Map), and Kalman Filters, the system constructs real-time maps while tracking the robot’s position. Integrated with Reinforcement Learning (RL) and Sensor Fusion, it enhances navigation in forests, disaster zones, and extreme conditions. Runs efficiently on Jetson Nano for real-time edge processing.</p>
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