Deep Learning Nanodegreee Foundation

My study notes and exercises for this course from Udacity. This course emphasis on breadth rather than depth by applying deep learning on plenty of applications.

• Syllabus:
  • Week 1 Linear Regression: Types of Machine Learning and when to use Machine Learning
    1. Welcome
    2. Anaconda
    3. Jupyter Notebook
    4. Applying Deep Learning
    5. Regression
  • *Week 2 Numerical Classification: Neural Network Architecture and Types 6. Siraj's Neural Network 7. Intro to Neural Networks 8. Project 1: Your First Neural Network: Bike Sharing
  • Week 3 Sentiment Analysis: Cloud Computing and Sentiment Analysis 9. Model Evaluation and Validation 10. Sentiment Analysis with Andrew Trask: Movie Reviews 11. Intro to TFLearn 12. Preparing for Siraj's Lesson 13. Siraj's Sentiment Analysis: Video Game Reviews, Game of Throne
  • Week 4 Recommender System: Math Notation and Recommender Systems 14. Siraj's Math Notations: Music Recommender System, Earthquake 15. MiniFlow: Boston House Pricing
  • Week 5 Data Preparation 16. Intro to Tensorflow: MNIST, notMNIST 17. Siraj's Data Preparation: Wine Dataset, Network Intrusion Dataset, MagnaTagATune Dataset, Speed Dating Data Prediction

* project week