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Part 1: Leaf Disease Detection using Deep Learning | Dataset Preparation + Image Visualization Welcome to Part 1 of the Leaf Disease Detection using Deep Learning tutorial series! 🌿 In this video, we’ll start our journey by preparing the dataset, processing leaf images, and visualizing sample data before moving on to model building. What You’ll Learn in This Video: ✅ How to collect and load the leaf disease dataset ✅ How to preprocess and normalize images for training ✅ How to visualize healthy vs. diseased leaves ✅ How to split data into training and validation sets ✅ A quick look at class distribution 📂 Topics Covered: Dataset collection and overview Data preprocessing and augmentation Data visualization with Matplotlib Preparing arrays for model input Project Overview: We’ll build a deep learning model to automatically detect leaf diseases using CNN-based architectures like VGG16, VGG19, and EfficientNetB4 — step by step. Next Video (Part 2): Model Building • Leaf Disease Detection | Part 2 – Model Bu... Series Playlist: 🔗 Part 1 – Dataset Preparation 🔗 Part 2 – Model Building 🔗 Part 3 – Training, Evaluation & Prediction Full project - https://www.aionlinecourse.com/ai-pro... Stay Connected: If you find this helpful, please like, comment, and subscribe for more deep learning projects! Got any questions? Drop them in the comments below. #deeplearning #aiprojects #computervision #transferlearning #tensorflow #machinelearning #aionlinecourse