Coursera Deep Learning Specialization

Deep Learning Specialization course material (e.g., lecture slides, quizzes, programming assignments), updating with my study progress.

Courses Outline

• Course 1: Neural Networks and Deep Learning

  • Week 1 - Introduction to Deep Learning
  • Week 2 - Neural Networks Basics
  • Week 3 - Shallow Neural Networks

• Course 2: Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

  • Week 1 - Practical Aspects of Deep Learning
  • Week 2 - Optimization Algorithms
  • Week 3 - Hyperparameter Tuning, Batch Normalization and Programming Frameworks

• Course 3: Structuring Machine Learning Projects

  • Week 1 - Machine Learning Strategy 1
  • Week 2 - Machine Learning Strategy 2

• Course 4: Convolutional Neural Networks

  • Week 1 - Foundations of Convolutional Neural Networks
  • Week 2 - Deep convolutional models: case study
  • Week 3 - Object detection
  • Week 4 - Special application: Face recognition & Neural style transfer

• Course 5: Sequence Models

  • Week 1 - Recurrent Neural Networks
  • Week 2 - Natural Language Processing & Word Embeddings
  • Week 3 - Sequence models & Attention mechanism

Notebooks

# TODO: update and index all notebooks

• Logistic Regression with a Neural Network Mindset
• Planar Data Classification with One Hidden Layer
• Building Your Deep Neural Network: Step by Step
• Deep Neural Network for Image Classification: Application
• Initialization
• Regularization
• Gradient Checking
• Optimization Methods
• TensorFlow Tutorial
• Convolutional Model: Step by Step
• Convolutional Model: Application
• Keras - Tutorial - Happy House
• Residual Networks
• Car Detection with YOLOv2
• Art Generation with Neural Style Transfer
• Face Recognition for the Happy House
• Building a Recurrent Neural Network - Step by Step
• Dinosaurus Land - Character-Level Language Model
• Jazz improvisation with LSTM
• Operations on Word Vectors
• Debiasing
• Emojify
• Neural Machine Translation with Attention
• Trigger Word Detection

Remarks

Some course resources are currently unavailable to download (e.g., Jupyter notebooks in Sequential Model course), which I collected from Kulbear.