Build YOLO Model from Scratch

Learning Objectives:

Upon completing this project, you will achieve the following learning objectives:

1. Understand Object Detection:

   • Gain a clear understanding of the concept of object detection in computer vision.

2. Configure YOLO V3:

   • Learn to configure and implement YOLO (You Only Look Once) version 3, a state-of-the-art object detection algorithm.

3. Make Inferences from YOLO on Real-time Images:

   • Acquire the skills to make real-time inferences using the YOLO model on images.

Files Contained in the Project:

• Build_YOLO_Model_from_scratch.ipynb: Jupyter notebook containing the project implementation and experimentation.

Usage:

1. Clone the repository:

git clone https://github.com/Praveen76/Build-YOLO-Model-from-scratch.git
cd Build-YOLO-Model-from-scratch

2. Open and explore the Jupyter notebook Build_YOLO_Model_from_scratch.ipynb to understand the project implementation.

3. Execute the code cells within the notebook to experiment with building a YOLO model from scratch.

4. Gain practical experience in configuring YOLO V3 and making real-time inferences.

Feel free to contribute, report issues, or suggest improvements!

Contributing

If you have a Data Science mini-project that you'd like to share, please follow the guidelines in CONTRIBUTING.md.

Code of Conduct

Please adhere to our Code of Conduct in all your interactions with the project.

License

This project is licensed under the MIT License.

Contact

For questions or inquiries, feel free to contact me on Linkedin.

About Me:

I’m a seasoned Data Scientist and founder of TowardsMachineLearning.Org. I've worked on various Machine Learning, NLP, and cutting-edge deep learning frameworks to solve numerous business problems.