Lec 12 : Vectorization of Logistic Regression and Standard Neural Net

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