I am sharing a complete list of latest ideas for final year students for their projects.
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Image Classification: Build an image classification model to categorize objects in images. Use popular datasets like CIFAR-10 or create your custom dataset.
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Sentiment Analysis: Create a sentiment analysis model to classify text data as positive, negative, or neutral sentiments. Use social media data or product reviews for training.
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Predictive Text Generation: Develop a model that generates coherent sentences or paragraphs of text. Use recurrent neural networks (RNNs) or transformers for this task.
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Chatbot: Build a chatbot that can hold conversations, answer questions, and provide assistance on various topics using natural language processing.
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Recommendation System: Create a recommendation system for movies, books, or products. Implement collaborative filtering or content-based approaches.
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Handwriting Recognition: Develop a model that recognizes handwritten characters or digits. You can use the MNIST dataset for this project.
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Object Detection: Build an object detection model to identify and locate objects in images or videos. Popular frameworks like YOLO or Faster R-CNN can be used.
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Anomaly Detection: Create an anomaly detection system to detect unusual patterns or outliers in data, which can be useful for fraud detection or network security.
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Face Recognition: Develop a face recognition system to identify and verify individuals in images or videos. Use libraries like OpenCV or face recognition libraries.
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Spam Email Classifier: Build a spam email classifier to automatically categorize emails as spam or not spam based on their content.
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Hand Gesture Recognition: Create a system that recognizes hand gestures for controlling devices or applications. This can be used for sign language recognition or gaming.
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Stock Price Prediction: Build a machine learning model to predict stock prices based on historical data and financial indicators.
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Disease Diagnosis: Develop a model for medical image analysis, such as detecting diseases from X-rays or MRIs.
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Speech Recognition: Create a speech recognition system that can convert spoken language into text. You can use libraries like SpeechRecognition or DeepSpeech.
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Autonomous Drone Navigation: Implement machine learning algorithms for autonomous drone navigation and obstacle avoidance.
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Predictive Maintenance: Build a model for predictive maintenance of machinery and equipment to detect when maintenance is needed before a breakdown occurs.
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Traffic Sign Recognition: Create a model that can recognize and classify traffic signs in images or videos, which can be used for self-driving cars or traffic management.
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Emotion Detection: Develop a system that can detect emotions from facial expressions in real-time video streams.
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Fake News Detection: Build a model to identify fake or misleading news articles using natural language processing and text analysis techniques.
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Natural Language Translation: Create a machine translation model that can translate text from one language to another, such as English to French or vice versa.