今天妙手偶得了一个非常好的机器学习平台End-to-End Machine Learning Library，这个平台是Brandon Rohrer创建的，里面用视频的方式介绍了机器学习的原理和应用。他的理念是：
The best way to learn new concepts is to use them to build something. These courses are structured to build foundational knowledge (100 series), provide in-depth applied machine learning case studies (200 series), and embark on project-driven deep-dives (300 series). Come have a look around and try one out today.
翻译成中文，就是：
学习新概念的最好方法是用它们来建造一些东西。这些课程的结构是建立基础知识(100系列)，提供深入的应用机器学习案例研究(200系列)，并开展项目驱动的深潜(300系列)。今天来看看，试一试吧。
对于机器学习的路径，他给出了关于神经网络、应用机器学习、数据可视化、数据科学等几个方面的推荐课程序列，非常值得借鉴。
Neural networks
193. How neural networks work
194. Build a neural network framework
195. Advanced neural network methods
196. Neural network optimization
Applied machine learning
197. How to choose a model
198. How optimization works
199. How selected models and methods work
200. Decision trees with Python an Pandas
201. Time-series analysis
202. Nonlinear modeling and optimization
Visualization
203. Navigating Matplotlib
204. Neural network visualization
Introduction to data science
206. Foundational skills
207. Data science concepts
208. Navigating a data science career
