If you really want to understand the capabilities and limitations of machine learning, you have to get hands-on. Here's a short list of options for beginners. The starting point differs for individuals based on their education and experience. However, the titles of resources may not necessarily reflect that fact. Following is a short list of resources with a bit of insight into their requirements and value. Deep learning, a subcategory of machine learning, has been omitted intentionally to keep the focus of this article on machine learning in general. Open ML (beta 2) describes itself as "an inclusive movement to build an open, organized, online ecosystem for machine learning". It builds open source tools for discovering and sharing data. Participants can pull the open data into their favorite machine learning environments and build models themselves or with the help of community data scientists.
https://www.informationweek.com/big-data/ai-machine-learning/how-to-get-hands-on-with-machine-learning/a/d-id/1335112
