Here is the Machine Learning Projects for Final Year students. This ideas shared after the development. You can use this for your final year project. This takes minimum one month to develop. If you have any enquiries contact us on whatsapp or Email.
Machine Learning Projects for Final Year students
- Real time face attendance system
- Human Emotion Recognition and Music Player
- Rice leaf disease detection
- Malaria infected cell detection
- Person Counting Camera for daily logs (For Railway Stations, Bus stations etc.)
- Any industrial part detection and counting system for identifying the count of daily production in industry
- Chatbot – Customized
- Car speed tracking
- Student information – Chatbot for Staff
- Tracking objects in Video
- Phishing sites detection
- AI based Home automation (without sensors- NO IOT)
- Cancel cell detection
- Malaria detection using deep learning
- Thyroid detection using deep learning
- Pneumonia cell detection using deep learning
- Brain tumor detection
- Plant recognition using deep learning
- Fruit recognition using deep learning
- Currency recognition for blind people
- Real-time Object Detection
- Live health monitoring system
- Android Smart Door lock
- Person following drone
- IOT Smart Dustbin
- Machine learning based home automation without sensors
- Camera Drone
- Baggage Tracker
- Facial recognition door with Raspberry pi
- Automated water tank fill for Home (If your water tank is empty or full, this system will automatically activate and deactivate the switch)
- IOT based baby monitoring system
- Food serving robot on dining table
- Human Following robot
- Path following robot
There are many machine learning projects that final year students can work on, depending on their interests and the resources available to them. Some examples include:
- Image classification: Develop a system that can automatically classify images into different categories, such as animals, plants, or vehicles. This project could involve using convolutional neural networks (CNNs) and transfer learning to achieve high accuracy on a dataset of images.
- Sentiment analysis: Develop a system that can automatically classify text as positive, negative, or neutral in sentiment. This project could involve using natural language processing (NLP) techniques such as tokenization and stemming, as well as machine learning algorithms such as naive Bayes and support vector machines (SVMs) to classify text data.
- Recommender system: Develop a system that can recommend items to users based on their past behavior and preferences. This project could involve using collaborative filtering or matrix factorization techniques to make recommendations.
- Anomaly detection: Develop a system that can detect anomalies in data, such as fraudulent transactions or equipment failures. This project could involve using techniques such as clustering, dimensionality reduction, and deep learning to identify patterns in the data that deviate from the norm.
- Time-series forecasting: Develop a system that can predict future values in a time-series data, such as stock prices, weather, or energy consumption. This project could involve using techniques such as exponential smoothing and ARIMA models to make predictions.
Any type of Android and Web Development Projects are available here.
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