video1.0<iframe src="https://www.loom.com/embed/b2aaffc5aaba410a8387693832cbe63f" frameborder="0" width="1680" height="1260" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>12601680Loomhttps://www.loom.com12601680https://cdn.loom.com/sessions/thumbnails/b2aaffc5aaba410a8387693832cbe63f-f6d83b0bf8f887fa.gif211.569In 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.