70+ Best and Unique Python Machine Learning Projects with source code [2023]

19 min readJun 6, 2023

In today’s blog, we will see some very interesting Python Machine Learning projects with source code. This list will consist of Machine learning projects, Deep Learning Projects, Computer Vision Projects, and all other types of interesting projects with source codes also provided.

Read the full article here — https://machinelearningprojects.net/python-machine-learning-projects/

Though textbooks and other study materials will provide you with all the knowledge that you need to know about any technology but you can’t really master that technology until and unless you work on some real-time projects.

In this tutorial, you will find 70+ Python Machine learning projects with source code for beginners, intermediates, and experts to gain real-world experience with this growing technology, Let’s do it…

Python Machine learning projects with source code

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. 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. 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.

6. Pedestrian Detection using HOGs

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, SSD, present out there, we don’t use HOGs much for object detection.

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 Machine learning project with source code for the final year.

8. 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.

9. 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.

10. 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

11. 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

12. 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.

13. 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

14. 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.

15. 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.

16. Wine Quality Prediction

In this blog, we will build a simple Wine Quality Prediction model using the Random Forest algorithm.

17. Face and eye detection 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.

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. Movie Recommendation System

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.

20. 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.

21. 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.

22. 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.

Deep Learning Projects with source code in Python

23. Google Stock Price Prediction using LSTM

In this project, we will see how we can perform Google’s stock price prediction using our Keras’ LSTMs model trained on past stock data. This project is just for educational purposes. Please do not invest your money using these models.

24. Image Captioning — with source code

In this project, we will implement the Image Captioning project which is a very advanced project. We will use a combination of LSTMs and CNNs for this use case.

This project can be your Machine learning project with source code for the final year.

25. Generating cifar-10 fake images using Deep Convolutional Generative Adversarial Networks (DCGAN)

In this project we will see how can we build some real-looking fake images, using Deep Convolutional Generative Adversarial Networks or DCGANs. GANs are basically known for their two networks, the Generative network, and the Discriminative network. We train our Discriminative model in such a way that it can tell us which image is real and which image is fake. The generative network tries to create new images that can even fool the Discriminator network and prove themselves to be real.

26. Helmet and Number Plate Detection and Recognition using YOLOv3

So guys in this project we will see how we can implement Helmet and Number Plate Detection and Recognition in Python using YOLO v 3 and some other Computer Vision techniques. This is a very advanced project which you can use for your college minor projects as well as major projects. So without wasting any further time.

Our main motive behind Helmet and Number Plate Detection and Recognition were to first detect if someone is wearing a helmet or not, if he is wearing it, no problem, but if not, detect his number plate and send an e-challan to him.

This project can be your Machine learning project with source code for the final year. I myself made this project my Final year’s minor project.

27. HealthCure — an all-in-one medical solution — medical project — 7 disease detections (Repeated)

These 7 detections are Covid Detection, Alzheimer Detection, Brain Tumor Detection, Breast Cancer Detection, Pneumonia Detection, Heart Disease Detection, and Diabetes Detection.

28. Invisible Man using Mask R-CNN

In this blog, we will see how we can perform Human Segmentation using Mask R-CNN. This is a very advanced project and many things are happening under the hood. Please try this project only when you are available with a GPU.

29. Neural Style Transfer

Who said that only humans can create beautiful artwork? In this blog, we will see how a neural network application called Neural Style Transfer can create beautiful artworks which even humans can’t think of.

30. Sudoku Solver

In this blog, we will see how we can implement Sudoku Solver using Computer Vision and Image Processing techniques. Sudoku is a 9X9 grid puzzle.

31. Human Segmentation using U-Net

In this blog, we will see how we can perform Human Segmentation using U-Net. U-Net is a very special CNN architecture that was specially made for segmentation in mainly the medical field. It is called a U-Net because of its special architecture whose shape is like U.

32. Milk Production prediction for next year using LSTM

In this blog, we will implement the Milk Production prediction for the next year with the previous 13-year milk production data. We will use LSTM for this project because of the fact that the data is Sequential.

33. Emotion Detector using Keras

In this blog, we will be building an Emotion Detector model in Keras using Convolutional Neural Networks. This is one of my favorite projects.

34. Monkey Breed Classification using Transfer Learning

In this blog, we will be using Transfer learning to implement our project that is Monkey Breed Classification. Transfer Learning is simply when we are using an already trained model for our current use case. In this case, we will be using Mobilenet, pre-trained on Imagenet.

35. MNIST Handwritten number recognition using Keras — with live predictor

When starting with Machine Learning, MNIST Handwritten number recognition comes as the first project in everyone’s mind because of its simplicity, abundant data, and magical results. It can also be thought of as the ‘Hello World of ML world. So, In this blog, we will see how to implement it.

You might be thinking, everyone has made a tutorial on it, so what’s special in this one. The special thing in my project is that I have also made a live interactive predictor at the end, where you will draw the number and our trained model will predict it.

MNIST Handwritten number recognition using Keras with live predictor

Blog Link - https://machinelearningprojects.net/harrys-invisibility-cloak/Machine Learning Projects:Link …

youtube.com

36. AI learns to play Flappy Bird Game

So, in this blog, we will implement the Flappy Bird Game which will be played by an AI. We will achieve this by using NEAT which stands for NeuroEvolution of Augmenting Topologies. One of the major fantasies of every machine learning engineer is to make a game that can learn to play on itself. In this blog, we will see how we can do that.

AI learns to play Flappy Bird Game - Python Project

Blog Link - https://machinelearningprojects.net/ai-learns-to-play-flappy-bird-game/Machine Learning Projects:Link …

youtube.com

37. Age Detection using CNN with Keras

In this blog, we will be implementing Age Detection using CNN with the help of Keras. This is going to be a very fun project.

38. Fire and Smoke Detection using CNN with Keras

So guys here comes the Fire and Smoke Detection project which is yet another very practical use case of Deep Learning. We will be using CNNs to implement this project. I have used Data Augmentation to increase the volume of my image dataset and I got a very satisfying accuracy of about 90% on a dataset like this.

You can further extend this idea by using it with a Raspberry Pi, a thermal sensor, and a camera for its practical implementation.

39. Cats and Dogs Classifier

In this blog, we will be building a Cats and Dogs Classifier using Convolutional Neural Networks. We have custom-made the architecture in this project. Here we have basically used 3 sets of Conv2D — BatchNormalization — Maxpooling — Dropout layers.

40. Dimensionality Reduction using Autoencoders

In this very interesting blog, we will see how we can perform Dimensionality Reduction using Autoencoders in the simplest way possible using Tensorflow.

Computer Vision Projects with source code in Python

41. Helmet and Number Plate Detection and Recognition using YOLOv3 (Repeated)

So guys in this project we will see how we can implement Helmet and Number Plate Detection and Recognition in Python using YOLOv3 and some other Computer Vision techniques. This is a very advanced project which you can use for your college minor projects as well as major projects. So without wasting any further time.

42. HealthCure — an all in one medical solution — medical project — 7 disease detections (Repeated)

These 7 detections are Covid Detection, Alzheimer Detection, Brain Tumor Detection, Breast Cancer Detection, Pneumonia Detection, Heart Disease Detection, and Diabetes Detection.

43. Invisible Man using Mask R-CNN (Repeated)

44. Sudoku Solver (Repeated)

In this blog, we will see how we can implement Sudoku Solver using Computer Vision and Image Processing techniques. Sudoku is a 9X9 grid puzzle.

45. Object Detection using SSD (Repeated)

46. Social Distancing using YOLOv3 (Repeated)

47. How to detect shapes using cv2

In this blog, we will see how we can detect shapes using cv2 in an image using contours and moments.

48. Document Scanner using OpenCV

So guys, in this blog we will see how we can build a very simple yet powerful Document scanner using OpenCV. This is one of my favorite projects because of its simplicity and its power. So without any further due.

In this blog, we will implement the Face Landmarks Detection project using the dlib library. We will perform both the 68-point and 5-point detections.

50. Make your Sketch using OpenCV in Python

In this very short blog, we will see how we can make our sketch using OpenCV in the simplest way possible. This is going to be a very fun project for beginners.

51. Face Recognition-based Attendance System (Repeated)

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.

52. How to perform Face Recognition using KNN

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 slightly less compared to these big boys like MTCNNs.

53. Immortal Snake game in Python using OpenCV

I have done plenty of projects to date in almost every domain of Data Science, from ML, DL, and Computer Vision to NLP, but this immortal snake game in Python is still one of my favorite projects because of its simplicity and user interaction. You will be totally amazed after watching the results in just around 100 lines of code.

54. How to find the most dominant colors in an image

In this blog, we will find the most dominant colors in an image using the KMeans clustering algorithm, this is a very interesting project and personally one of my favorites because of its simplicity and power.

55. How to perform 5 most famous types of thresholding techniques

A simple blog in which we will be performing the 5 most famous types of thresholding techniques. These 5 techniques are THRESH_BINARY, THRESH_BINARY_INV, THRESH_TOZERO, THRESH_TOZERO_INV, and THRESH_TRUNC

56. Face and eye detection in cv2 using Haarcascades

So in this very interesting blog, 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.

57. Harry’s Invisibility Cloak — less than 50 lines of code

So guys, one of the most awaited blogs is here. Today we are going to code Harry’s Invisibility Cloak in less than 50 lines of code and you will be totally amazed after watching the results. Yeah Yeah, I know you can’t control your emotions.

58. How to split and merge channels in cv2

This blog is going to be a very simple and short blog where we will see how we can input an image and split and merge channels in cv2.

59. Rotating and Scaling Images in cv2 — a fun application in Python

In this blog, we are gonna make a very fun application in Python in which we will be Rotating and Scaling Images in cv2. This is going to be a very simple and interesting project

60. How to use mouse clicks to draw circles in Python

In this very short blog, we will see how we can use mouse clicks to draw circles in Python using OpenCV.

61. How to repair damaged images using inpainting methods

In this blog, we will see how we can repair damaged images in Python using inpainting methods of OpenCV. This is gonna be a very fun project, So without any further due, let’s dive into it.

Image inpainting is the process of removing damage, such as noises, strokes, or text, on images. It is particularly useful in the restoration of old photographs which might have scratched edges or ink spots on them. These can be digitally removed through this method.

62. How to generate a negative image in Python using OpenCV

So, in this blog of this OpenCV series we are going to generate a negative image. Talking about negatives, it’s a very nostalgic feeling because nowadays we are not used to seeing negatives but about 10–15 years earlier, first of all, negatives were generated and then the original images.

63. How to detect edges using Laplacian 2nd order derivative

In this blog of this OpenCV series, we are going to implement a Laplacian High Pass Filter or Laplacian 2nd order derivative for images which is a very useful image processing mostly used in defense domains (in missiles or tanks) to track down enemy’s tanks and trucks and destroy them.

64. How to plot a Histogram of a grayscale image in 2 ways

In this very short blog, we will see how we can plot a histogram of a grayscale image. The first way is using NumPy and the second way is using matplotlib

65. How to denoise an Image using Median Blur

In this blog, what we will be seeing will not be something less than magic. You will be amazed after watching the power of Median Blur.

66. How to perform Morphological Operations like Erosion, Dilation, and Gradient in Python using OpenCV

So, in this blog, we will see how we can perform morphological operations like erosion, dilation, and gradient upon an image to enhance it.

Morphological transformations are some simple operations based on the image shape. It is normally performed on binary images. It needs two inputs, one is our original image, the second one is called structuring element or kernel which decides the nature of the operation. Two basic morphological operators are Erosion and Dilation. Then its variant forms like Opening, Closing, Gradient, etc also come into play.

67. How to quickly detect contours in an Image in Python using OpenCV

In this blog, we will see how we can detect contours in an image using the cv2 module. Talking about contouring it is a very useful operation when our use case involves geological terrain images or studying weather maps, etc.

68. Blurrings in cv2 — Simple Blur, Box Blur, Gaussian Blur, and Median Blur

In this blog, we will see how to perform the most famous 4 types of Blurrings in cv2 (Simple Blur, Box Blur, Gaussian Blur, and Median Blur).

Natural Language Processing Projects with source code in Python

69. Words to Vectors using Spacy — proving King-Man+Woman = Queen

This blog is going to be a very short blog where we will see the magic of Words to Vectors using Spacy library and also we will prove that King-Man+Woman = Queen. This is going to be a very interesting blog

70. Topic Modeling using Latent Dirichlet Allocation

So guys in this blog we will see how we can perform topic modeling using Latent Dirichlet Allocation. What we do in Topic Modeling is we try to club together different objects(documents in this case) on the basis of some similar words. This means that if 2 documents contain similar words, then there are very high chances that they both might fall under the same category.

71. Fake news Classifier using LSTM

In this blog, we will be implementing a Fake news Classifier using Embeddings and LSTM layers of Keras library. We have custom-made the architecture in this project.