1.Neural Networks and Deep Learning
1.2.1 Python Basics with numpy-(optional)
1.2.2 Logistic Regression with a Neural Network mindset
1.3.1 Planar data classification with a hidden layer
1.4.1 Building your Deep Neural Network Step by Step
1.4.2 Deep Neural Network Application Image Classification
2.Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
2.1.1 Initialization
2.1.2 Regularization
2.1.3 Gradient_Checking
2.2.1 Optimization
2.3.1 Tensorflow Tutorial
3.Structuring Machine Learning Projects
4.Convolutional Neural Networks
4.1.1 Convolutional Neural Networks Application
4.2.1 Keras Tutorial - The Happy House (not graded)
4.2.2 Residual Networks
4.3.1 Car detection with YOLOv2
4.4.1 Art generation with Neural Style Transfer
4.4.2 Face Recognition for the Happy House
5.Sequence Models
5.1.1 Building a Recurrent Neural Network
5.1.2 Dinosaurus Island -- Character-level language model - (final) - learners
5.1.3 Improvise a Jazz Solo with an LSTM Network
5.2.1 Operations on word vectors
5.2.2 Emojify
5.3.1 Neural machine translation with attention - v4
5.3.2 Trigger word detection