100 Days of Deep Learning - AdaGrad Explained in Detail with Animations | Optimizers in Deep Learning Part 4

Adaptive Gradient Algorithm (Adagrad) is an algorithm for gradient-based optimization. The learning rate is adapted component-wise to the parameters by incorporating knowledge of past observations. 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 00:15 - Adaptive Gradient Introduction 03:42 - Elongated Bowl Problem 07:22 - Visual Reprensation 09:42 - How do Optimizers behave? 17:22 - Mathematical Intuition 24:20 - Disadvantage 26:16 - Outro