What are some good machine learning projects for final year?

1. Image Classification: This project involves taking a set of images and using machine learning algorithms to classify them into different categories. By utilizing image processing techniques, the algorithm should be able to identify objects within an image, differentiate between various scenes and label the images accordingly.

2. Natural Language Processing (NLP): Natural language processing is one of the most popular projects for final year students due to its broad range of applications in daily life such as natural language understanding (NLU) systems and voice-enabled digital assistants like Alexa or Siri. The goal is to develop models that can interpret human speech accurately so they can respond appropriately depending on the context of the question or command given.

3. Sentiment Analysis: Sentiment analysis is used by businesses to analyze customer opinions about their products or services in order to gain insights and improve customer experience. The goal is to create a model that can process text data from online reviews or other sources, identify sentiment behind those comments (positive/neutral/negative), then output it in a usable format for further analysis by companies.

4 Predictive Analytics: Predictive analytics uses historical data combined with machine learning algorithms to predict future outcomes or events from current trends and patterns found in past data sets. This type of project could involve building a model that detects credit card fraud by analyzing purchase patterns over time, detecting malignant tumors via medical imaging, predicting stock prices given current market conditions, etc..

1. Classification of medical images: In this project, a machine learning model could be created to classify medical images such as X-Rays and MRIs into different categories based on certain parameters such as tumor size or type of injury. The model could then be used to help diagnose patients quickly and accurately.

2. Image recognition using facial recognition technology: In this project, the goal would be to create a facial recognition system that can identify individuals based on their features. This could have applications in security or verifying identity for certain purposes such as online banking or unlocking devices with face ID.

3. Natural language processing (NLP): Using NLP technology, computers can be trained to understand text input from human users and take proper actions accordingly. An example of an NLP project is building an AI chatbot which can answer questions about products and services from customers, thereby reducing the need for customer service staff and increasing efficiency greatly.

4. Recommender systems: These are systems which recommend items such as songs, movies, books etc., depending on user’s preference by analyzing large amounts of data about user’s past behavior collected over time using machine learning techniques like clustering and classification algorithms. These recommender systems are used extensively by companies such as Netflix, Amazon etc., providing personalized experiences to each user while generating more revenue at the same time due to increased user engagement with their products/services offered through these recommender systems.