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Deep Learning specialization by deeplearning.ai

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Deep Learning Specialization on Coursera

This is my personal projects for the course. The course covers deep learning from begginer level to advanced. Through five interconnected courses, this develop a profound knowledge of the hottest AI algorithms, mastering deep learning from its foundations (neural networks) to its industry applications (Computer Vision, Natural Language Processing, Speech Recognition, etc.). Instructor: Andrew Ng, DeepLearning.ai

Course 1. [Neural Networks and Deep Learning]

  1. Week1 - [Introduction to deep learning]
  2. Week2 - [Neural Networks Basics]
  3. Week3 - [Shallow neural networks]
  4. Week4 - [Deep Neural Networks]

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

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

Course 3. [Structuring Machine Learning Projects]

  1. Week1 - [Introduction to ML Strategy] - Setting up your goal - Comparing to human-level performance
  2. 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]

  1. Week1 - [Foundations of Convolutional Neural Networks]
  2. 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
  3. [Week3 - Object detection] - Papers for read: You Only Look Once: Unified, Real-Time Object Detection, YOLO
  4. Week4 - [Special applications: Face recognition & Neural style transfer] - Papers for read: DeepFace, FaceNet

Course 5. [Sequence Models]

  1. Week1 - [Recurrent Neural Networks](
  2. Week2 - [Natural Language Processing & Word Embeddings](
  3. Week3 - [Sequence models & Attention mechanism]

Learn Tensorflow and Deep Neural Network

  • I recommend you a video course for learning tensorflow from Google here
  • A good introduction about Deep Neural Network, download here
  • Best results on standard dataset like MNIST, CIFAR-10/100, ILSVRC2012... here
  • Keras Documentation Chinese Version here
  • Deep Learning by Goodfellow here

Some Good Machine Learning Tutorial

  • Expectation Maximization(EM) course by Xu Yida on Youtube

Other useful links

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