Top 20 Machine Learning Project Ideas for Final Year with Source Code

Machine learning is one of the most exciting and rapidly growing fields in the world of technology. I am going to present you Top 20 Machine Learning Project Ideas for Final Year. These Final Year Projects will help you to select a Machine learning Project for your final Year. You don’t need to make these projects from scratch as I will provide source code of these projects.

Why you should select Machine Learning Project for Final Year?

Selecting a Project in final year is very important as this is very important for your grades and future life. These ML projects can help you showcase your skills and knowledge in data science and artificial intelligence. It will also help you in getting job after your education. Machine Learning projects can help you get more chances and make your resume look better. Final year students who want to work in data science or machine learning should do a project to learn how to use machine learning models in real life.

In simple words, e-commerce means buying and selling products via the Internet. So, e-commerce sales forecasting is a system that helps to predict the future sales of products or services. This prediction is based on various business data. With the help of this system you quickly meet the customer expectations and help the business plan its inventory, marketing, and pricing strategies. Forecasting allows you to make accurate restock predictions based on product demand and consumer purchasing patterns. Doing this ensures that you always have products in stock and are ready to ship when clients need them.

To build this project, you should know the basics of machine learning because this project is complex, but from a final year point of view, this project is perfect.

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Today fake messages, internet scam are growing day by day. And phishing is also an internet scam and in this scam attackers sends a fake messages. These fake messages that look come out from the trusted sources. This projects help to detect the phishing attack and also it protects clients from phishing fraud by helping them recognize and block fake websites. This prevents the theft of important information. Organizations also benefit by maintaining their brand and reputation. So, as a final year project selection this project is best and if you are choosing these kinds of project you will get great grades in final year.

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As a final year project, you can develop a gesture recognition interface that will help you enable direct communication between humans and machines. Traditional methods, such as keyboards and mouse, can limit communication between humans and machines. So, this project used machine learning techniques and infrared information to detect and classify hand gestures. The system consists of several stages: hand detection, gesture segmentation, feature extraction, gesture classification using five pre-trained convolutional neural network models and vision transformer, and human-machine interface design. To build this system, you can use several machine learning algorithms like support vector machine, K nearest neighbor, decision tree, and neural networks to recognize gestures.

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In the future, humanoid robots will live in our homes and help us with our daily tasks by handling objects. So, we developed a system used in machine learning and computer vision techniques to enable the robots to perceive and interact with their environment in real time. This system trains machine learning models, often based on YOLO, to recognize objects from a large dataset. These models are then embedded into the robotic system, allowing it to make predictions on the fly. The robot takes pictures with its cameras while moving, and its machine-learning model quickly identifies and categorizes objects, allowing the robot to react immediately. This final year project is exciting, and I also personally like it. So, what are you thinking? Choose this project and get good grades in the final year project.

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The rise of social media and online platforms has made spreading fake news a big problem. To tackle this problem news problem, you can develop a fake news detection system. This system will use AI algorithms to predict whether the news is fake. Twitter(X) is also working on this system to make their tweets authenticated and credible. To make this system, download a dataset from Kaggle and apply the machine learning algorithm. You can develop it in Python, but in case if you want it as a web-based system, then you can create it in Django(the Framework of Python)

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Heart disease is a common and serious health issue that affects millions of people worldwide. It refers to a range of conditions that affect the heart, including coronary artery disease, heart attacks, and heart failure. Heart disease can lead to significant health problems, such as stroke,
arrhythmias, and even death. It is a leading cause of death in many countries and has a significant impact on the quality of life of those who suffer from it. The Heart Disease Dataset is a valuable resource for
researchers and healthcare professionals who are interested in understanding the risk factors associated with heart disease and developing effective diagnostic and treatment strategies.
Heart disease is a complex and multifactorial condition, with various risk factors contributing to its development, such as age, genetics, lifestyle, and underlying health conditions. Recent advances in machine learning
and data analysis techniques have provided new opportunities for predicting and detecting heart disease. By analysing large datasets of patient attributes and health outcomes, researchers can develop
predictive models that can identify patients at high risk of heart disease and improve treatment outcomes.

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7. Image caption generator using machine learning algorithms

This project describes images in text form, and some people who use text-based content can’t access them. You know that pictures contain very important information. So, the image caption generator automatically generates descriptions for images and makes visual content that is more accessible to everyone. This project uses a deep learning model to generate captions for images based on their content and context. Building this system used three main algorithms: convolutional neural networks (CNN), recurrent neural networks (RNN), and sentence production. As a final year project, it is good and not very complex.

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8. Intelligent customer support chatbot

Today, in every business, customers demand fast answers and 24/7 hours of self-service. Sometimes, business owners have limited resources, and it is difficult to fulfil growing customer demands. The intelligent customer support chatbot helps improve customer satisfaction and streamline operations. This application interacts with the customer through natural language and provides them with relevant information the customer wants. It will use machine learning techniques such as natural language processing, sentiment analysis, and deep learning to understand the customer’s query, context, and emotions and generate appropriate responses. This project is helpful for any business, like an e-commerce business or any other business that meets customer requirements and customer support. This also increases business efficiency.

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Nowadays, most people like music, but music composition often requires training and expertise, limiting the accessibility of music to trained musicians. And there is a growing need for new and original music content in different industries, which is a challenge for composers. With the help of machine learning technology, build an AI music composer that can generate musical compositions with other instruments and styles based on some input or prompt. As a final year project, it is exciting and entertaining. This system uses deep neural networks, such as Generative Adversarial Networks (GANs), to learn the patterns of harmony, rhythm, and style from a large dataset of MIDI files. With the help of this advanced algorithm system, new and original music can be created by predicting the following notes.

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A stock market is a public marketplace where you can purchase and sell shares of publicly traded corporations. So, this final year project predicts the future value of the stock market. As you know, market value fluctuates every minute. So, this system using machine learning helps to predict the future value based on the historical data of the stock market. It can help investors and traders to make better decisions in the stock market. To build this system, you should understand the long and short-term memory network. This model enables to predict the stock prices.

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11. Multilingual Language Translation

Multilingual Language Translation

Multilingual Machine Translation is a computer system that translates text from one language to another. It is important for global communication and is increasingly used by researchers. Now automated systems can replace human expertise in some areas. Machine learning can help to learn from large amounts of data, adapt to new languages and domains, and generate fluent and natural translations.

To make a multilingual language translation system using machine learning use machine learning frameworks and libraries, such as PyTorch or TensorFlow, to implement and train your neural machine translation model.

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With the rise in the digital world, credit card fraud has become challenging. Many fraudsters use phishing websites to steal your credit card information. This is not a threat only to users. It is also a threat to business owners. This fraud can harm business credibility. You can develop a credit card fraud detection system as your final year project to stop this. First, data from Kaggle will be collected, and then a machine learning algorithm will be applied to find which algorithm is best and provides the best accuracy.

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13. Medical Image Diagnostics Assistant

In the medical field, medical images are very important for patients or doctors. In medical field sometimes faces difficulties when interpreting medical images because medical data is complex, and there is a risk of human error. Building this system uses machine learning algorithms to analyze and interpret medical images such as X-rays, CT scans, or MRI scans and provide diagnoses or recommendations for the patients or doctors. It can help improve the accuracy, efficiency, and accessibility of medical image diagnostics. This system used a convolutional neural network CNN. This project is also helpful for doctors to easily scan for patients. As a final year student this project is also beneficial in future.

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14. Autonomous Vehicle Navigation

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Autonomous vehicles are also known as self-driving vehicles. This autonomous vehicle navigation is capable of fulfilling human transportation capabilities. It uses real-time object detection to help vehicles understand their surroundings, make decisions, and navigate safely without human input. Building this system, machine learning can help to learn from large amounts of data, adapt to dynamic and complex environments, and optimize the safety and efficiency of the vehicle. This system uses sensors such as a camera, LiDAR, radar, or GPS from a reliable source, such as a simulator or an actual vehicle. Building this final year project uses machine learning models such as convolutional neural networks, recurrent neural networks, or reinforcement learning that can handle multimodal and sequential data.

15. Sentiment analysis of twitter data

Sentiment analysis of twitter data

Social media platforms attract huge numbers of users. Many user-generated data is being created on social networking sites like Twitter. This data, which includes comments and reviews, is valuable for studying people’s reactions and opinions on various topics. Twitter-based Sentiment Analysis (TSA) has become famous for understanding people’s sentiments and opinions. Twitter has around 300 million active users, making it one of the most popular microblogging sites. This information is helpful for product sales, stock market movements, and election results. So, this final year project aims to build a system that identifies the human emotions and opinions expressed in text. This system uses machine learning models to collect the tweets-related data, classify them as positive, negative, or neutral, and evaluate the results. This final year project is very unique and exciting. So, you should select this project.

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16. Movie Recommendation system

The entertainment industry has grown significantly, with a large amount of content created daily. So, in that case, viewers faced difficulty selecting the most suitable movie. For this, they developed a movie recommendation system that allows users to choose their movies. This system’s primary goal is to make personalized movie recommendations to users. This final-year project is simple to build. We want to solve the problem of choosing a movie to watch. Viewers often need help because there are so many options. It’s even harder because everyone has different preferences.

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17. Image based plant disease detection system

In agriculture science, plant disease is widespread day by day. And you know that food demand is increasing daily due to the increasing population. This final year project helps the farmer detect plant disease with the help of plant images. This system used advanced machine learning algorithms to detect the plant’s disease efficiently. The main goal of this system is to help the farmers monitor the plant’s health and provide healthy food to the people.

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Today, the world of the internet and social media provides a platform where people freely express their opinions and thoughts in text form. But some people used their freedom in the wrong way to direct hate towards individuals for race, religion and many more things. For this, cyber security organizations increase the number of cases day by day for cyberbullying. Also, many organizations have found a solution to detect hateful speech. This final year project is beneficial, exciting, and unique. This project used machine learning algorithms to detect hateful and offensive speech through this system.

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19. Customer Segmentation using Machine Learning

Customer Segmentation using Machine Learning

A customer segmentation project means dividing the customer and making a group according to various customer characteristics, like 30-plus age group customers in one group and 40-plus age customers in another group. It helps organizations to understand their customers better. Knowing the variations between customer groups makes making strategic decisions about product development and marketing easier. Building this system using a machine learning algorithm is the best tool to analyze customer characteristics based on training from machine learning model data. It helps to analyze customers and characterize different groups.

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20. Wind Power and Electric Load Forecasting

Wind Power and Electric Load Forecasting

This final year project uses wind power and electric load using machine learning techniques to predict the electricity demand and the renewable energy generation in a power system. With the help of this system, we can predict future electricity generation from the wind turbines. It is also essential for ensuring the power grid’s reliability, efficiency, and sustainability, especially with the growing use of wind and solar energy. Some various methods and algorithms can be used for wind power and electric load forecasting, such as ARIMA and NARX models, which are based on time series analysis and can capture the periodicity and correlation of the data—in this final year’s project also used the advanced machine learning algorithms.

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Absolutely! The suggested projects are meant to spark your creativity. Feel free to tailor the projects to align with your passion and interests within the realm of machine learning.

Providing source code is crucial for two reasons. Firstly, it helps you understand the implementation details of the project. Secondly, it allows others to learn from your work, contributing to the collaborative nature of the machine learning community.

Consider creating a detailed project report that outlines the problem statement, methodology, implementation details, and results. Additionally, include the source code and any insights or lessons learned during the project. This comprehensive approach will showcase your skills and dedication

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