jJayyyyyyy / Coursera-Deep-Learning-Specialization

Andrew Ng(吴恩达)

Deep Learning Specialization

介绍

这是coursera上吴恩达老师开设的深度学习专业课程，课件，作业，测验都在这里，供大家参考。

课程资源

• Course 1: Neural Networks and Deep Learning
  • 课件
    • 1. Introduction to Deep Learning
    • 2. Neural Networks Basics
    • 3. Shallow Neural Networks
    • 4. Deep Neural Networks
  • 测验
    • Week 1 Quiz - Introduction to deep learning
    • Week 2 Quiz - Neural Network Basics
    • Week 3 Quiz - Shallow Neural Networks
    • Week 4 Quiz - Key concepts on Deep Neural Networks
  • 作业
    • 1. Logistic Regression with a Neural Network mindset
    • 2. Python Basics With Numpy
    • 3. Planar data classification with one hidden layer
    • 4. Building your Deep Neural Network Step by Step
    • 5. Deep Neural Network Application
  • 知识点小结
• Course 2: Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
  • 课件
    • 1. Practical aspects of Deep Learning
    • 2. Optimization algorithms
    • 3. Hyperparameter tuning, Batch Normalization and Programming Frameworks
  • 测验
    • Week 1 Quiz - Practical aspects of deep learning
    • Week 2 Quiz - Optimization algorithms
    • Week 3 Quiz - Hyperparameter tuning, Batch Normalization, Programming Frameworks
  • 作业
    • 1. Initialization
    • 2. Gradient Checking
    • 3. Regularization
    • 4. Optimization methods
    • 5. Tensorflow Tutorial
  • 知识点小结
• Course 3: Structuring Machine Learning Projects
  • 课件
    • 1. ML Strategy_1
    • 2. ML Strategy_2
  • 测验
    • Week 1 Quiz - Bird recognition in the city of Peacetopia (case study)
    • Week 2 Quiz - Autonomous driving (case study)
  • 作业
  • 知识点小结
• Course 4: Convolutional Neural Networks
  • 课件
    • 1. Foundations of Convolutional Neural Networks
    • 2. Deep convolutional models case studies
    • 3. Object detection
    • 4. Special applications Face recognition & Neural style transfer
  • 测验
  • 作业
    • 1. Convolution model Step by Step
    • 2. Convolution model Application
    • 3. Keras Tutorial Happy House
    • 4. Residual Networks
    • 5. Autonomous driving application Car detection
    • 6. Face Recognition for the Happy House
    • 7. Art Generation with Neural Style Transfer
  • 知识点小结
• Course 5: Sequence Models
  • 课件
    • 1. Recurrent Neural Networks
    • 2. Natural Language Processing & Word Embeddings
    • 3. Sequence models & Attention mechanism
  • 测验
  • 作业
    • 1. Building a Recurrent Neural Network Step by Step
    • 2. Dinosaurus Island Character level language model final
    • 3. Improvise a Jazz Solo with an LSTM Network
    • 4. Emojify
    • 5. Operations on word vectors
    • 6. Neural machine translation with attention
    • 7. Trigger word detection
  • 知识点小结

里程碑

2018.12.1完成，yeah！