[Latest] 20+ Top Machine Learning Projects for final year
Hey guys, we will see some of the Best and Unique Machine Learning Projects for final year engineering students in today’s blog. Machine learning has become a transformative technology across various fields, revolutionizing complex problem-solving.
Read the full article here — https://machinelearningprojects.net/machine-learning-projects-for-final-year/
For final-year students pursuing a degree in computer science or related disciplines, engaging in machine learning projects can be an excellent way to consolidate theoretical knowledge, gain practical experience, and showcase their skills to potential employers.
In this article, we will explore exciting machine learning projects for final year students, highlighting their relevance, potential applications, and the skills they can help develop.
This is going to be a very interesting blog, so without any further due, let’s do it…
1. HealthCure — an all-in-one medical solution — medical project
This is a project that I chose as my college’s final year major project and guess what, it went pretty well. This project uses various advanced techniques like CNNs, VGGs, XGBoost, etc for performing 7 disease detections. This is one of the best Machine Learning Projects for final year in Python.
7 disease detections:
- Covid-19 Detection
- Brain Tumour Detection
- Breast Cancer Detection
- Alzheimer Detection
- Diabetes Detection
- Pneumonia Detection
- Heart Disease Detection
Snapshot of Covid-19 Detection Page
These 7 detections are Covid Detection, Alzheimer Detection, Brain Tumor Detection, Breast Cancer Detection, Pneumonia Detection, Heart Disease Detection, and Diabetes Detection.
This project can be your B.Tech. final year Machine learning project. I myself made this as my final year major project.
Working video of our App
How to run Healthcure App
2. Leaf Disease Detection Flask App
Leaf disease detection is a critical issue for farmers and agriculturalists. The detection of leaf diseases at an early stage can help prevent the spread of diseases and ensure a better yield. However, manual detection of leaf diseases is time-consuming and often inaccurate. With the advancement of technology, machine learning, and computer vision techniques can be used to develop automated solutions for leaf disease detection.
In this article, we will discuss the development of a Leaf Disease Detection Flask App that uses a deep learning model to automatically detect the presence of leaf diseases.
Main Screen
Result Screen
Working Video of our App
3. Youtube Comments Extraction and Sentiment Analysis Flask App
Hey, guys in this blog we will implement Youtube Comments Extraction and Sentiment Analysis in Python using Flask. It is going to be a very interesting project.
Snapshots of our App
Home Screen
Results Screen
Wordcloud
Working of our Youtube Comments Extraction and Sentiment Analysis App…
- On the main page, we first enter/paste a youtube video url whose comments we need to analyze.
- Then we click on the ‘Analyse Comments’ button.
- As soon as we hit the above button, our scrapper starts scraping comments from that video.
- Now that we have a list of all the scraped comments, we will then clean these comments and run a sentiment analysis model on these cleaned comments.
- A list of these cleaned comments along with their sentiment is sent on the results page.
- All the POSITIVE sentiment comments have a green background, all NEGATIVE sentiment comments have a red background and all NEUTRAL comments have a gray background.
- In the menu bar, we have a wordcloud option that will open up a wordcloud (as shown above) created accordingly from the scraped comments for a respective video.
Working Video of our App
4. Realtime Number Plate Detection using Yolov7
Hey guys, in this blog we will see how to perform Number Plate Detection using YOLOv7 by training the YOLOv7 on our custom number plate data.
YOLOv7 is the new state-of-the-art real-time object detection model.
You can use it for different industrial applications. Also, you can optimize the model, that is, converting the model to ONNX, TensorRT, etc, which will increase the throughput and run the edge devices.
Sneak at our Number Plate Detection using Yolov7
5. Background Remover Flask App using Python
Hey guys, in this blog we will see how we can build a background remover flask app using Python. So without any further due, let’s do it…
Result Samples
Example 1:
Example 2:
Working Video of our App
6. Object Detection using SSD
In this blog, we will use Single Shot Detections for performing Object Detection using SSD in the simplest way possible. SSDs are very fast in Object Detection when compared to those big boys like R-CNN or Fast R-CNN, etc. This is going to be a very fun project with endless use cases.
7. Social Distancing using YOLOv3 — Object Detection
This is also a very advanced project in which I used object detection on a camera’s live feed or video to check if Social Distancing is being followed or not in a locality. This project also has endless future scopes.
Working Video of our App
This project can be your B.Tech final year Machine learning project.
8. Face Recognition-Based Attendance System — Flask App — With GUI
So guys here comes the most awaited project of machine learning Face Recognition-based Attendance System. As the name says this project takes attendance using biometrics (in this case face) and is one of the most famous projects among college students out there. I have tried to make the project the easiest way possible.
Snapshots of our App…
Face Recognition-based Attendance System Home Page…
List Users Page…
Attendance Sheet
Working Video of our App
9. Self-Organizing Maps
In this blog, we will see how we can implement self-organizing maps in Python. This is going to be a very short blog. So without any further due, Let’s do it…
Final Results…
10. Pedestrian Detection using HOGs in Python
In this project, we will perform pedestrian detection using HOG short for Histogram for Gradients. HOGs are great feature detectors and can also be used for object detection with SVM but due to many other State of the Art object detection algorithms like YOLO, and SSD, present out there, we don’t use HOGs much for object detection.
11. IPL Score Prediction with Flask app
In this project, I built an IPL Score Prediction model using Ridge Regression which is just an upgraded form of Linear Regression. We have the IPL data from 2008 to 2017. We will also be building a beautiful-looking interactive Flask model.
Working Video of our App
12. Weight Category prediction using Random Forest
In this project, I performed the weight category prediction of a person given height, weight, and gender with the help of the Random Forest algorithm.
Checkout the code walkthrough
13. How to perform Face Recognition using KNN
So in this blog, we will see how we can perform Face Recognition using KNN (K-Nearest Neighbors Algorithm) and Haar cascades. Haar cascades are very fast as compared to other ways of detecting faces (like MTCNN) but with an accuracy tradeoff. Its accuracy is a bit less when compared with these big boys like MTCNNs.
We will be seeing 2 scripts in this blog:
- The first is for adding a new face.
- The second is for real-time Face Recognition using KNN.
14. Flight Price Prediction with Flask app — with data visualizations
So guys this is yet another one of the most favorite projects of mine. In this blog, I implemented a Flight Price Prediction model using different techniques and also I performed very frequent data visualizations to better understand our data.
Working Video of our App
15. House Price Prediction — USA Housing Data
House Price Prediction Project proves to be the Hello World of the Machine Learning world. It is a very easy project which simply uses Linear Regression to predict house prices. This is going to be a very short project.
Checkout the code walkthrough
16. Stock Sentiment Analysis using headlines
In this project, we will see how we can perform stock sentiment analysis using the headlines of a newspaper. We will predict if the stock market will go up or down. This is a simple but very interesting project due to its prediction power.
17. Wine Quality Prediction
In this blog, we will build a simple Wine Quality Prediction model using the Random Forest algorithm.
Checkout the code walkthrough
18. Bank Note Authentication using Random Forest
In this blog, we will see how we can perform Bank Note Authentication or how we can classify Bank Notes into fake or authentic classes based on numeric features like variance, skewness, kurtosis, and entropy.
19. Flipkart Reviews extraction and sentiment analysis with Flask app
This is a very interesting blog where we will be performing Flipkart Reviews extraction and sentiment analysis and also we will be building a beautiful-looking Flask app to show everything.
Working Video of our App
20. How to find the most dominant colors in an image using KMeans clustering
In this blog, we will find the most dominant colors in an image using the K-means clustering algorithm, this is a very interesting project and personally one of my favorites because of its simplicity and power.
Check out the demo here…
21. Movie Recommendation System in 2 ways
Basically, I have performed Movie Recommendation System using two different ways. In the 1st way, we will use a user-movie matrix to find similarities.
The simple intuition of this 2nd way is that we will be combining the main features like the cast, director, genres, etc., and observe similarities between them because most of the time similar directors make similar movies, similar casts like to perform in some similar specific types of movies.
22. Credit Card Fraud Detection
In this blog, we will be building a Credit Card Fraud Detection model which will be very simple and easy to understand. This is a very basic machine learning project which students basically do in their starting phase of machine learning.
23. Face and Eye detection in cv2 using Haarcascades
A simple project in which we will see how we can perform face and eye detection in cv2 using Haarcascades. This is going to be a very easy and fun project. Remember it’s only detection and not recognition.
Check out the demo here…
24. Spam Detection using Count Vectorizer
In this blog, we will see how we can perform Spam detection in the simplest way possible with the help of a Count Vectorizer and Multinomial Naive Bayes algorithm.
Check out the demo here…
25. House Tax Prediction using Random Forest — Boston Housing Data
We will use the Random Forest algorithm to predict house tax. This is a simple project. I have used Boston Housing Data for this use case.
Check out the demo here…
Bonus Project:
Doctor-Patient Appointment System in Python using Flask
Hey guys, in this blog we will see a Doctor-Patient Appointment System for Hospitals built in Python using Flask. It is a very interesting project with lots of functionalities. So without any further due, let’s do it…
Main Page
On the main page, we have total 5 options:
- Patient Login
- Doctor Login
- Admin Login
- Patient Registration
- Doctor Registration
Patient Registration Page
- This is the Patient Registration Page where a Patient can register himself/herself by entering his/her details.
- The details that are needed are First Name, Last Name, Date of Birth, Phone No, Login Password, and Address.
- The Login Password should be of at least 8 characters and should contain numbers and alphabets.
- As soon as the Patient fills in all his details and clicks on the Register button, the registration request is sent to the super admin who can either approve or delete the registration request.
Doctor Registration Page
Conclusion
Engaging in machine learning projects during the final year of study can significantly enhance students’ skills, knowledge, and employability. These projects not only provide hands-on experience but also demonstrate students’ ability to tackle real-world problems using machine learning techniques. Whether students choose sentiment analysis, predictive maintenance, healthcare diagnosis, fraud detection, or recommendation systems, each project offers unique opportunities to explore diverse domains and contribute to technological advancements. Embrace these projects as stepping stones towards a successful career in machine learning, where skills and creativity can make a difference.
So these were some of the best and most unique Machine Learning Projects for final year students.
Check out my Machine Learning, Deep Learning, OpenCV, NLP, and Flask projects.
