This video develops the concept of Forward and backward Propagation in Neural Networks by using Simple example of logistic. Computations are illustrated using Computational Graph discussed in previous lecture.
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Neural Nets and Deep Learning Lec 8: Gradient Decent for Logistic Regression
Neural Nets and Deep Learning Lec 9: Computational Graphs for Studying Neural network
Neural Nets and Deep Learning Lec 10-11 : Forward and Back-propagation in Logistic Regression
Lec 12 : Vectorization of Logistic Regression and Standard Neural Net
Neural nets and Deep Learning Lec 13: Types of Neurons and Their properties I
Neural nets and Deep Learning Lec 14A: Softmax
Lec 14 B : Keras Implementation of Standard neural network
Neural Nets and Deep learning Lec 15 : Evaluation of Binary Classifiers
Lec 16A : Precision Recall Curve
Lec 16B : Keras Implementation of Multi class Classification using Standard Neural Net
Lec 17 : Introduction to Convolution Neural Networks
Lec 18 A : CNN 2 : Strides and Convolution on Volumes