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Introduction
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Classroom Contents
Deep Learning Indepth Tutorials With Krish Naik
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- 1 Introduction
- 2 AI vs ML vs DL vs Data Science
- 3 Why Deep Learning Is Becoming Popular?
- 4 Introduction To Perceptron
- 5 Working Of Perceptron With Weights And Bias
- 6 Forward Propogation,Backward Propogation And Weight Updateion Formula
- 7 Chain Rule Of Derivatives
- 8 Vanishing Gradient Problem
- 9 Different types Of Activation Functions
- 10 Different types Of Loss functions
- 11 Different type Of Optimizers
- 12 Practical Implementation OF ANN
- 13 Black Box Models VsWhite Box Models
- 14 Convolutional Neural Network
- 15 Practical Implementation Of CNN
