Unsupervised Learning Strategies for a CNN: Pytorch Deep Learning Tutorial

TIMESTAMPS: 00:00 - Video Intro 01:05 - Video Overview: What is Unsupervised Learning? 02:47 - Method 1: Classifying Image Rotation 11:40 - Using Image Rotation Pre-trained Model to Fine-tune Image Classification 14:45 - Method 2: Classifying Shuffled Images/Puzzle Solving 19:52 - Using Puzzle Solving Pre-trained Model to Fine-tune Image Classification 22:00 - Final Remarks Donations https://www.buymeacoffee.com/lukeditria Discord Server: https://discord.gg/8g92X5hjYF GitHub Repository (Section 6) https://github.com/LukeDitria/pytorch_tutorials In this comprehensive tutorial, we delve into the world of deep learning with ResNet architectures and custom datasets. Join us as we explore the fundamentals of ResNet models, understanding its intricate architecture, and how to implement it using PyTorch. We'll guide you through the process of creating custom datasets, transforming data, and training the ResNet model. Learn about dynamic learning rate scheduling to optimize your model's performance over epochs. Prerequisites: - Basic knowledge of neural networks and deep learning concepts. - Familiarity with PyTorch and Python programming. Whether you're a beginner or an experienced developer, this tutorial provides valuable insights into advanced neural network architectures and their practical applications. Don't forget to like, share, and subscribe for more engaging tutorials on AI, machine learning, and programming.