deeplearning.ai Specialization

This repository contains all the lecture slides and solutions of all the programming assignments and quizzes of all the courses offered at Coursera Deep Learning Specialization.

Instructor: Andrew Ng, DeepLearning.ai

Course 1. Neural Networks and Deep Learning

• Week1 - Introduction to deep learning
• Week2 - Neural Networks Basics
• Week3 - Shallow neural networks
• Week4 - Deep Neural Networks

Course 2. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization

• Week1 - Practical aspects of Deep Learning - Setting up your Machine Learning Application - Regularizing your neural network - Setting up your optimization problem
• Week2 - Optimization algorithms
• Week3 - Hyperparameter tuning, Batch Normalization and Programming Frameworks

Course 3. Structuring Machine Learning Projects

• Week1 - Introduction to ML Strategy - Setting up your goal - Comparing to human-level performance
• Week2 - ML Strategy (2) - Error Analysis - Mismatched training and dev/test set - Learning from multiple tasks - End-to-end deep learning

Course 4. Convolutional Neural Networks

• Week1 - Foundations of Convolutional Neural Networks
• Week2 - Deep convolutional models: case studies - Papers for read: ImageNet Classification with Deep Convolutional Neural Networks, Very Deep Convolutional Networks For Large- Scale Image Recognition
• Week3 - Object detection - Papers for read: You Only Look Once: Unified, Real-Time Object Detection, YOLO
• Week4 - Special applications: Face recognition & Neural style transfer - Papers for read: DeepFace, FaceNet

Course 5. Sequence Models

• Week1 - Recurrent Neural Networks
• Week2 - Natural Language Processing & Word Embeddings
• Week3 - Sequence models & Attention mechanism

Reference

https://www.coursera.org/specializations/deep-learning