100 Days of Deep Learning - Pretrained models in CNN | ImageNET Dataset | ILSVRC | Keras Code

A pre-trained model is a model created and trained by someone else to solve a problem that is similar to ours. In practice, someone is almost always a tech giant or a group of star researchers. They usually choose a very large dataset as their base datasets such as ImageNet or the Wikipedia Corpus. Then, they create a large neural network (e.g., VGG19 has 143,667,240 parameters) to solve a particular problem (e.g., this problem is image classification for VGG19). Of course, this pre-trained model must be made public so that we can take these models and repurpose them. Notes: https://learnwith.campusx.in/s/store/courses/YouTube%20Notes ============================ Do you want to learn from me? Check my affordable mentorship program at : https://learnwith.campusx.in ============================ 📱 Grow with us: CampusX' LinkedIn: https://www.linkedin.com/company/campusx-official CampusX on Instagram for daily tips: https://www.instagram.com/campusx.official My LinkedIn: https://www.linkedin.com/in/nitish-singh-03412789 Discord: https://discord.gg/PsWu8R87Z8 👍If you find this video helpful, consider giving it a thumbs up and subscribing for more educational videos on data science! 💭Share your thoughts, experiences, or questions in the comments below. I love hearing from you! ⌚Time Stamps⌚ 00:00 - Intro 01:11 - Why use pre-trained models? 04:19 - ImageNET Dataset 09:16 - ILSVRC 13:24 - Architecture of AlexNET 15:05 - Famous Architectures 17:45 - Idea of pre-trained models 21:20 - Code Example