00.Machine Learning
Grew out of work in AINew capability for computers Examples:Database mining Large datasets from growth of automation/web. E.g.,Web click data,medical records,biology,engineeringApplications can’t program by hand. E.g.,Autonomouos helicopter,handwriting recognition,most of Natural Language Processing(NLP),Computer VisionSelf-customizing programs E.g.,Amazon,Netflix product recommendationsUnderstanding human learning(brain,real AI).
01.Machine learning algorithms:
Supervised learning the idea is that we’re going to teach the computer how to do something.unsupervised learning we’re going let it learn by itself. Others: Reinforcement learning, recommender systems. Also talk about:Practical advice for applying learning algorithms. ⭐You have all these tools,but the more important thing,is to learn how to use have all these tools these tools properly.There’s a huge difference between people that know how to use these machines learning algorithms,versus people who don’t know how to use these tools well. ⭐⭐You must have a good grasp of the basics and understand the differences between various machine learning algorithms. 学习这些基本的机器学习知识只是打基石，如何熟练的使用各种算法或者改进算法解决实际问题才是进阶能力。
