ncsu data science track

, dive into one of the "live competitions currently running Onkaggle and give all-you has learnt a try!Step 8: Deep LearningNow so you had learnt most of the machine learning techniques, it was time to give deep learning a shot. There is a good chance that's already know what's deep learning, and if you still need a brief intro, here it's.I am myself new to deep learning, so please take the these suggestions with a pinch of salt. The most comprehensive resource is deeplearning.net. You'll find e

There are thousands of packages and hundreds of functional formulas in the field of data science, although you don't need to know all of this, but it's important to have a quick look at your study. Learning Big Data includes understanding of statistics, math, programming knowledge (especially R, Python, SQL), and understanding the business to drive decisions. The

http://blog.csdn.net/pipisorry/article/details/44245575A good article on how to learn python and use Python for data science, data analysis, and machine learning Comprehensive(integrated) Learning Path–data Science in PythonJourney from a pythonnoob(Novice) to a kaggler on P

the retention rate of active players over a period of time.For example, one of your games has successfully acquired 4,000 players thanks to some marketing behavior. On the 5th day, if the number of active players in the game reached 2000 on the day, the retention rate is 50%, if the next day (6th day) existing players reduced by 10% to 1800 people, then the 6th day game retention rate is 45%, and so on.In general, developers will count the retention rates for the first day of the game, the 7th