Deep Dive in AlexNet: Paper Reading, Notes and Python Implementation | Paper with Code | скачать в хорошем качестве

Deep Dive in AlexNet: Paper Reading, Notes and Python Implementation | Paper with Code |

In this video, we’ll explore the AlexNet architecture from both a theoretical and practical standpoint. First, you’ll learn how to read and analyze a deep learning research paper, extract key details, and take effective notes. Next, we’ll discuss the dataset, delve into the AlexNet structure (covering padding, stride, and filters), and examine how to calculate each layer’s operations. Finally, we’ll implement the AlexNet model step by step in Python. Follow along with the timestamps below, and don’t forget to check out the GitHub repository linked here for the complete code: https://github.com/mudassar266/CNN-St... Timestamps • 00:00 – Introduction • 00:47 – How to read deep learning paper • 01:30 – Dataset description • 02:14 – AlexNet architecture • 04:42 – Important formula • 05:53 – Padding • 07:11 – Stride • 08:08 – Filters • 09:37 – Paper outcomes • 11:24 – Calculations between layers • 15:12 – Python implementation Enjoy the video and feel free to leave your questions or comments below. Your support helps the channel grow, so remember to like, share, and subscribe!