授课教师: Andrew Ng
内容:
- Week 1: Introduction to deep learning
- Week 2: Neural Networks Basics
- Week 3: Shallow neural networks
- Week 4: Deep Neural Networks
内容:
- Week 1: Practical aspects of Deep Learning(Initialization, Regularization and Gradient Check)
- Week 2: Optimization algorithms
- Week 3: Hyperparameter tuning, Batch Normalization and Programming Frameworks (Introduction to Tensorflow)
内容:
- Week 1: ML Strategy (1)
- Week 2: ML Strategy (2)
内容:
- Week 1: Foundations of Convolutional Neural Networks
- Week 2: Deep convolutional models: case studies
- Week 3: Object detection
- Week 4: Special applications: Face recognition & Neural style transfer
内容:
- Week 1: Recurrent Neural Networks
- Week 2: Natural Language Processing & Word Embeddings
- Week 3: Sequence models & Attention mechanism
推荐课程笔记:http://kyonhuang.top/Andrew-Ng-Deep-Learning-notes/#/
课程主要分为两部分:校园讲座和在线讲座。在线部分就是由DeepLearning.ai制作的深度学习网络课程,包括所有的在线编程作业;校园讲座的内容与在线部分不重叠,一半lecture会讨论偏策略的内容,另一半讲了GANs、强化学习、聊天机器人等技术,整体难度大于在线课程部分。
课程主页:http://cs230.stanford.edu/
In-Class Lecture地址:http://onlinehub.stanford.edu/cs230
Online Lecture地址:https://www.coursera.org/specializations/deep-learning
- Class introduction & Logistics
- Deep Learning Intuition
- Full-cycle of a Deep Learning Project
- Adversarial Attacks / GANs
- AI+ Healthcare
- Deep Learning Project strategy - Case studies
- Interpretability of Neural Network
- Career Advice / Reading Research Papers
- Deep Reinforcement Learning
- Chatbots / Closing Remarks