Tonight, before the exchange began within half an hour, about 30, 40 coming in the problem. After the start of the exchange, he has been to play with blood-like, knock from 8:30 to 10:00, a total of more than 20 exchange problem. After now, there are several problems still remain in the mind.
1, data analysts and data scientists What is the difference, data analysts need to understand the need of machine learning and deep learning?
2, data analysis and data mining What is the difference?
3, liberal arts students want to switch to do data analysis, how to do?
Before you can send an article of reference within our number: liberal arts students in English professional background, Python and reptiles still play slip
4, data cleansing general operating procedures?
5, the general operating characteristics of engineering paradigm?
These small issues above interested partners, can be found under their own. Later, we slowly explore together, because not to eat, so eat food that went.
There's little time partner, you can click to read the original , as I point a praise.