Python Projects with Source Code – Practice Top Projects in Python

Python Projects with Source Code

Looking to build a career in Python? Want to improve your resume with multiple personal projects on it? Then this blog of Python projects with source code is for you. You earlier read about the top 5 data science projects; now, we bring you 6 projects implementing data science with Python. In this blog, you’ll find the entire code to all the projects. Read on to give your data science/ Python career a head-start.

List of amazing Python Projects with source code –

Why do Projects in Python?

In an interview, a resume with projects shows interest and sincerity. Spending time on personal projects ultimately proves helpful for your career. In this blog of python projects, we try our best to include different data science and machine learning libraries of Python to give you a better experience.

Top Python Projects with Source Code

Let’s start discussing python projects with source code –

1. Driver Drowsiness Detection with OpenCV and Keras

Intermediate python project - driver drowsiness detection system

Driving while the driver feels drowsy is extremely dangerous and thousands of accidents happen each year because the driver fell asleep. The drowsiness detection system can save a life by alerting the driver when he/she feels drowsy.

This python project is implemented using OpenCV and Keras. With OpenCV, we are detecting the face and eyes of the driver and then we use a model that can predict the state of a person’s eye “Open” or “Close”. The classification of eyes is done by a Convolutional Neural Network (CNN) model which is a deep neural network we build in Keras. CNN works extremely well for image classification purposes and this is why our model is based on CNN.

The project looks interesting. Isn’t it? Check the complete implementation of the Intermediate Python Project on Drowsiness Detection System with Source Code

2. Detecting Fake News with Python

python project - detecting fake news

Fake news can be dangerous. This is a type of yellow journalism and spreads fake information as ‘news’ using social media and other online media. This is a common way to achieve a certain political agenda. Fake news may contain false and/or exaggerated claims. Social media algorithms often viralize these and create a filter bubble. In this, we will train on a news.csv dataset of shape 7796×4. We’ll mainly use two things- a TfidfVectorizer and a PassiveAggressiveClassifier. A TfidfVectorizer turns a collection of raw documents into a matrix of TF-IDF features. And a PassiveAggressiveClassifier is an online learning algorithm that stays passive for a correct classification and becomes aggressive when there’s a miscalculation.

Please refer – Detecting Fake News with Python for the complete implementation of the python project with source code. 

3. Speech Emotion Recognition with librosa

Python project

Speech Emotion Recognition (SER) is an attractive application of data science today as we constantly attempt to give the consumer a better experience. This includes recognizing human emotion and affective states from speech. Since voice often exposes underlying emotions with tone and pitch, it can be used to understand the users’ needs and use it to improve the service. We will use the RAVDESS dataset and the libraries librosa, soundfile, and sklearn to build a model using an MLPClassifier. In most projects, we use Jupyter Lab to run our code.

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Ready to build your own model? Speech Emotion Recognition Python Project with Source Code

4. Detecting Parkinson’s Disease with XGBoost

Python machine learning project

Parkinson’s disease is a progressive disorder of the central nervous system that affects over 1 million people in India every year. It affects movement and can be a cause of tremors and stiffness. This is a neurodegenerative disorder with 5 stages to it, and affects dopamine-producing neurons in the brain. In this python project, we will use the UCI ML Parkinsons dataset and use XGBClassifier from xgboost to build a model that can accurately detect the presence of Parkinson’s disease in a person. We will also use the libraries scikit-learn, numpy, and pandas.

Check the complete python project with source code – Detecting Parkinson’s Disease with Python 

5. Gender and Age Detection with OpenCV

Python project age and gender detection

Computer Vision is a field of study enabling computers to see and recognize digital images and videos- this is something only humans (and animals) are generally capable of. This involves processes like object recognition, video tracking, motion estimation, and image restoration. It is exciting to be able to predict a person’s gender and age from just a photograph. CNNs (Convolutional Neural Networks) are often the choice when we work with images. In this project, we’ll use OpenCV (Open Source Computer Vision) and implement deep learning, using trained models on the Adience dataset.

This is just a brief, explore detailed Gender and Age Detection Python Project with source code

6. Breast Cancer Classification with Keras

project in python - breast cancer classification

IDC (Invasive Ductal Carcinoma) is the most common form of breast cancer, forming about 80% of all breast cancer diagnoses. This is a cancer that develops in milk ducts, and then invades the fibrous/fatty breast tissue outside them. In this project, we use the IDC_regular dataset (with breast cancer histology images). Histology is the study of the microscopic structure of tissues. With 2,77,524 patches of size 50×50 from 162 whole mount slide images scanned at 40x, we’ll learn to build a classifier to train on 80% of the dataset. We’ll use 10% of it for validation. We’ll be using Keras to define a CNN (CancerNet).

Excited? Check the entire python project of breast cancer classification with source code


We have learned to build 6 exciting python projects with source code. Try them at your own end and pay attention to every step as you do it. Which one was your favorite? Tell us in the comment. 

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5 Responses

  1. Robin Sharma says:

    Thanks for all projects. It will be very helpful for me to learn python.

  2. rahul giri says:

    I follow from starting this is the best way to learn python or data science with project it’s to much helpful for beginners and also developer .

  3. Teklebrhan Aregawi says:

    it is very nice!

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