{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/b2aaffc5aaba410a8387693832cbe63f\" 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/b2aaffc5aaba410a8387693832cbe63f-f6d83b0bf8f887fa.gif","duration":211.569,"title":"14-Advanced Sensor Flow and Keras: Mastering Custom Layers and Training Techniques 🚀","description":"In this video, I delve into Advanced Sensor Flow and Keras, covering topics like higher-order derivatives with nested gradient tapes, custom gradients, and building operations from scratch. We explore the implementation of layers such as 2D convolution and batch normalization, and I demonstrate how to create reusable layers using Keras. Additionally, I discuss advanced architectures like ResNet and transformer blocks, and I showcase custom training loops essential for complex setups like GANs. Finally, I present a practical demo where we integrate these concepts into a mini ResNet model for digit classification. I encourage you to engage with these advanced techniques and consider how they can enhance your projects."}