How to Classify Images using Pytorch Hub Yolov5 | Animals Classification Ultralytics YoloV5 tutorial

In this tutorial, we dive into the world of image classification using YOLOv5 and PyTorch. Learn how to train YOLOv5 on a custom dataset, leveraging the power of Ultralytics' implementation on GitHub. From understanding the basics to advanced techniques, we cover everything from setting up YOLOv5 PyTorch environment to testing the model on your own images.

This tutorial has 4 parts :

🔍 Download and prepare the data : We'll start by downloading the images, and preparing the dataset for the train

🐍Create Conda enviroment and all the relevant Python libraries .

🛠️ Training : Run the train over our dataset

📊 Testing the Model: Once the model is trained, we'll show you how to test the model using a new and fresh image

You can download the code here : XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

More relevant content in this playlist : https://www.youtube.com/playlist?list=PLdkryDe59y4aCcCN4ioFpdLVAGZ_dFeFr

A perfect course for learning modern Computer Vision with deep dive in TensorFlow , Keras and Pytorch . You can find it here : http://bit.ly/3HeDy1V 
I also recommend this book, https://amzn.to/44GnlLW : "Make Your Own Neural Network - An In-depth Visual Introduction For Beginners ".
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00:00 Introduction 
00:15 Download the data
01:03  Build the Model - Transfer learning 
09:54 Test The Model 
~~~~~~~~~~~~~~ Credits ~~~~~~~~~~~~~ 
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