Programming Assignments _{Deep Learning Andrew Ng}

Solutions manual to accompany Deep Learning Specialization on Coursera.

Course A - Neural Networks and Deep Learning

Week 2 - Neural Networks Basics

• Python Basics with numpy (optional)
• Logistic Regression with a Neural Network mindset

Week 3 - Shallow Neural Networks

• Planar data classification with a hidden layer

Week 4 - Deep Neural Networks

• Building your Deep Neural Network: Step by Step
• Deep Neural Network - Application

Course B - Improving Deep Neural Networks

Week 1 - Practical Aspects of Deep Learning

• Initialization
• Regularization
• Gradient Checking

Week 2 - Optimization Algorithms

• Optimization

Week 3 - Hyperparameter Tuning and Batch Normalization

• TensorFlow

Course D - Convolutional Neural Networks

Week 1 - Foundations of Convolutional Neural Networks

• Convolutional Model: step by step
• Convolutional Model: application

Week 2 - Deep Convolutional Models: case studies

• Keras Tutorial (not graded)
• Residual Networks

Week 3 - Object Detection

• Car detection with YOLO

Week 4 - Special Applications: Face Recognition & Neural Style Transfer

• Art generation with Neural Style Transfer
• Face Recognition

Course E - Sequence Models

Week 1 - Recurrent Neural Networks

• Building a recurrent neural network - step by step
• Dinosaur Island - Character-Level Language Modeling
• Jazz improvisation with LSTM

Week 2 - Natural Language Processing & Word Embeddings

• Operations on word vectors - Debiasing
• Emojify

Week 3 - Sequence Models & Attention Mechanism

• Neural Machine Translation with Attention
• Trigger word detection