{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/bf6a29119be94528b8cad0c26650b67b\" frameborder=\"0\" width=\"1680\" height=\"1260\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1260,"width":1680,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1260,"thumbnail_width":1680,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/bf6a29119be94528b8cad0c26650b67b-96608001d1f9af71.gif","duration":283.301,"title":"11-Introduction to PyTorch Neural Networks: From Fundamentals to Advanced Techniques","description":"In this video, I walk you through the PyTorch Neural Networks Tutorial, building on our previous work with NumPy. We start with tensor fundamentals, covering creation, reshaping, and operations, before diving into the powerful Autograd feature for automatic differentiation. I demonstrate how to construct neural networks from scratch using basic PyTorch tensors and then transition to high-level APIs for easier model management. We also explore complete training examples, including best practices for data loading and model evaluation. I encourage you to follow along with the examples and apply these concepts to your own projects."}