Vanishing/Exploding Gradients are two of the main problems we face when building neural networks. Before jumping into trying out fixes, it is important to understand what they mean, why they happen and what problems they cause for our neural networks. In this video, we will learn what it means for gradients to vanish or explode and we will take a quick look at what techniques there are in order to deal with vanishing or exploding gradients.
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❓To get the most out of the course, don't forget to answer the end of module questions:
https://fishy-dessert-4fc.notion.site/Deep-Learning-101-Questions-35797462583d43a3adcea9478bfe035d
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https://fishy-dessert-4fc.notion.site/Deep-Learning-101-Answers-f90449595add492fb9dd8db3859662e3
RESOURCES:
🏃♀️ Data Science Kick-starter mini-course: https://www.misraturp.com/courses/data-science-kick-starter-mini-course
🐼 Pandas cheat sheet: https://misraturp.gumroad.com/l/pandascs
📥 Streamlit template (updated in 2023, now for $5): https://misraturp.gumroad.com/l/stemp
📝 NNs hyperparameters cheat sheet: https://www.misraturp.com/nn-hyperparameters-cheat-sheet
📙 Fundamentals of Deep Learning in 25 pages: https://misraturp.gumroad.com/l/fdl
COURSES:
👩💻 Hands-on Data Science: Complete your first portfolio project: https://www.misraturp.com/hods
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