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The Optimizer
Neural Networks: Deep Dive
Solving a Real-World Problem: Revisiting Model-3
- Building a 3-Layer Neural Networks using basic arithmetic and analyzing its accuracy
- Understanding the limitations of simple mathematical operations
- Preparing for more sophisticated optimization techniques
Forward Propagation of Input Data & Backward propagation of errors
- Back-propagation of Errors
- Unveiling the powerful optimization algorithm that drives AI learning
- Understanding the flow of information and gradients through networks
Improving the accuracy of NN by replacing basic arithmetic with calculus
- Introduction to gradient-based optimization
- Understanding derivatives and their role in learning
- Implementing calculus-based learning algorithms