100 Days of Deep Learning - Gradient Descent in Neural Networks | Batch vs Stochastics vs Mini Batch Gradient Descent

This video breaks down Batch, Stochastic, and Mini-Batch methods, explaining their impact on the learning process. Discover the differences between them in simple terms. Notes: https://learnwith.campusx.in/s/store/courses/YouTube%20Notes Code used - https://colab.research.google.com/drive/131xWdpUiy_f87tN0dRpKaEvOxR9DoiSB?usp=sharing ============================ 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! ✨ Hashtags✨ #NeuralNetworks #GradientDescent #MachineLearning #DeepLearning #DataScience #AI #LearningBasics #simplifiedlearning ⌚Time Stamps⌚ 00:00 - Intro 00:42 - Gradient Descent 03:05 - Back Propagation Algorithm 90:00 - Batch Gradient Descent 15:25 - Questions/Differences 16:30 - Code Demo 19:29 - Which is faster to converge? 23:30 - Stochastic Gradient Descent 30:09 - Vectorization 31:02 - Mini Batch Gradient Descent 35:00 - Why batch size is provided in multiple of 2 36:12 - What if batch size doesn't divide number of rows? 37:10 - Code Demo 37:42 - Outro