Author(s): Souradip Pal

Originally published on Towards AI.

From “Impossible” to “Easy” — Build Your Own Image Classifier in Just a Few Steps!

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Imagine if you could build a computer program that looks at a picture and tells you, “Yes, that’s a bird!” 🐦

Not so long ago, this kind of image recognition was considered nearly impossible — it was even the punchline of a joke in the tech world! Fast forward to today, and with deep learning, building an image classifier is not only possible but also surprisingly simple.

In this tutorial, we’ll create a basic bird classifier using Python and deep learning libraries. Whether you’re a beginner or just curious, this step-by-step guide will show you how to teach a computer to recognize a bird. Plus, all of this can be done for free on platforms like Kaggle. Ready? Let’s dive in! 🚀

Before we start, it’s crucial to ensure that internet access is enabled on Kaggle. Since using external resources is necessary, this step is a must!

Code:

import socket, warningstry: socket.setdefaulttimeout(1) socket.socket(socket.AF_INET, socket.SOCK_STREAM).connect(('1.1.1.1', 53))except socket.error as ex: raise Exception("STOP: No internet. Click '>|' in top right and set 'Internet' switch to on")

🔍 Explanation: This code snippet checks your internet connection by attempting to connect to a public DNS server. If it fails, you’ll… Read the full blog for free on Medium.

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Published via Towards AI