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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

Remarks

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

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