Gradient Descent in Neural Networks | Batch vs Stochastics vs Mini Batch Gradient Descent
Channel: CampusX
Date: 2022-04-14

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.

Digital Notes for Deep Learning: https://shorturl.at/NGtXg

Code used - https://colab.research.google.com/drive/131xWdpUiy_f87tN0dRpKaEvOxR9DoiSB?usp=sharing

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✨ 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