Hey, guys in this blog we will see some of the Best End to End Machine Learning Projects with source codes. This is going to be an interesting blog, so without any further due, let’s start…
Machine learning has revolutionized various industries, from healthcare to finance and everything in between. However, building a machine learning model involves more than just training algorithms. It requires a systematic approach that encompasses problem definition, data collection, preprocessing, model training, evaluation, and deployment. This holistic process is known as an end to end machine learning project.
Best End to End Machine Learning Projects with source codes
1. HealthCure – medical project – 7 disease detections
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 in Python.
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 Machine learning project with source code for the final year. I myself made this as my final year major project.
Working video of our App
How to run Healthcure App
2. 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. Although it is not an ML Project, 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
3. 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
4. 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. So without any further due, let’s do it…
YouTube is one of the most popular video-sharing platforms in the world, with over 2 billion monthly active users. As a result, it generates a massive amount of data in the form of comments, which can provide valuable insights into the user’s opinion about a particular video or topic. In this article, we will discuss a project on YouTube comments extraction and sentiment analysis using Python and Flask.
Home Screen
Results Screen
Wordcloud
Working Video of our App
5. 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.
6. 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
7. Flight Price Prediction with Flask app
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
8. 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
Conclusion
End-to-end machine learning projects are a vital component of the data science journey. They provide a structured approach to solving complex problems and help bridge the gap between theory and practical implementation. By following the outlined steps and best practices, data scientists can develop robust machine learning models that have a real impact in various industries.
Do let me know if there’s any query regarding end-to-end Machine learning projects with source code by contacting me by email or LinkedIn.
FAQs
1. What programming languages are commonly used in end-to-end machine learning projects?
Python is widely used in the machine learning community due to its rich ecosystem of libraries such as TensorFlow, scikit-learn, and PyTorch.
2. Are there any prerequisites for learning end-to-end machine learning projects?
A basic understanding of machine learning concepts and programming skills are beneficial. However, there are resources available for beginners to get started.
3. Can end-to-end machine learning projects be applied to specific domains like healthcare or finance?
Absolutely! The end-to-end approach can be applied to any domain where predictive modeling is required.
4. How long does it take to complete an end-to-end machine learning project?
The duration varies depending on the complexity of the project, the size of the dataset, and the experience of the data science team. It can range from a few weeks to several months.
5. Where can I find open-source machine learning projects with source codes to practice?
Platforms like GitHub and Kaggle provide a wide range of open-source machine learning projects with source codes that you can explore and learn from.
Check out my other machine learning projects, deep learning projects, computer vision projects, NLP projects, Flask projects at machinelearningprojects.net