Abstract
Impy is an open-source Data Science project. Impy is a Python3 library with features that help you in your computer vision tasks. Impy is a library used for deep learning projects that use image datasets. It is built using Python, Machine Learning. The complete source code is publicly available on GitHub under the Apache License 2.0, making it a useful reference for students building a Data Science mini project or final-year project.
1. Introduction
Impy is a library used for deep learning projects that use image datasets.
Email: lozuwaucb@gmail.com Bug reports: https://github.com/lozuwa/impy/issues
Impy has multiple features that allow you to solve several different problems with a few lines of code. In order to showcase the features of impy we are going to solve common problems that involve both Computer Vision and Deep Learning.
2. Objective
Impy is a Python3 library with features that help you in your computer vision tasks.
This project demonstrates how Python, Machine Learning can be applied to a real-world Data Science problem.
4. Technology Stack
5. System Requirements
General requirements for this technology stack — check the README for exact versions.
- Python 3.8 or later
- pip / virtualenv for dependencies
- VS Code, PyCharm or Jupyter Notebook
- Git (to clone the repository)
6. Installation & Setup
git clone https://github.com/lozuwa/impy.git
cd impyFull setup instructions are in the project README.
7. Future Enhancements
Suggested extensions you can add to make this your own project.
- Turn the analysis into an interactive dashboard
- Automate data refresh with a scheduled job
- Add a predictive model on top of the analysis
8. Viva / Review Questions
Common questions examiners ask for projects in this domain.
- What is the source of the dataset and how was missing data handled?
- Which exploratory analysis steps revealed the most useful insight?
- Why were these particular charts chosen to present the data?
- Which statistical or ML technique supports the conclusions?
- How could the analysis be automated or refreshed with new data?
9. Source Code & License
This project is developed by lozuwa and published on GitHub under the Apache License 2.0. Please follow the license terms and credit the original author when you use or modify this code.
Want to build this as your internship project?
Work on a Data Science project like this with mentor guidance, weekly reviews and an internship certificate from Training Trains, Erode — online or offline.
Apply for Data Science Internship