Neural Networks and Deep Learning basics
Logistic Regression
Neural Network overview
Gradient Descent and Back Propagation
Deep Neural Networks
Improving Deep Learning
Bias and variance, regularization, normalization
Gradient checking
Optimization algorithms
Hyperparameter tuning
Batch normalization
Neural Networks and Deep Learning
Multi class classification, ML strategy
Transfer, multi task, end-to-end learning
Convolutional Neural Networks
Convolution, padding, stride
Convolution over volumes
Pooling, why convolution
Classic networks
Transfer learning
Residual networks
Object localization and detection
Code
Logistic Regression
Building your Deep Neural Network
Deep Neural Network Application
Initialization
Regularization
Gradient Checking
Optimization methods
Tensorflow Tutorial
Convolution model
Convolution application
Keras tutorial
Residual network
Recurrent neural network