Load & Display Image Dataset from Google Drive in Colab | Artificial Intelligence Tutorial Series 1

Welcome to Episode 1 of our Artificial Intelligence Image Classification Tutorial Series! In this video, we kick off our machine learning journey by connecting Google Drive to Google Colab and loading image datasets organized in subfolders — a crucial first step in building real-world classification models. You’ll learn how to: ✅ Mount Google Drive in Colab ✅ Access datasets stored in structured folders (e.g., Cat/, Dog/) ✅ Read and visualize sample images ✅ Prepare your dataset environment for training deep learning models Whether you're working on a Kaggle competition, academic project, or portfolio model, this video sets the foundation for scalable image classification pipelines. Code to mount and link dataset in google colab(Copy and paste code to link to google drive): from google.colab import drive drive.mount('/content/drive') main_folder = '/content/drive/MyDrive/Colab Notebooks/pet' if os.path.exists(main_folder): subfolders = os.listdir(main_folder) print(f"✅ Connected to: {main_folder}") print(f"📁 Subfolders found: {subfolders}") else: print("❌ Folder path does not exist.")