- There have been not a few lists of “representative methods in data science” ever.
- Below is my personal list of statistical and machine learning methods that every data scientist should know in 2016.
- I feel some of them are already out-of-date because they appear to neglect the latest advance of data science in the industry.
- From my experience in the data science industry for 4 years, I think that currently these 12 methods are the most popular, useful and suitable for various problems requiring data science.
- In addition to the list itself, I showed R or Python scripts of an experiment on sample datasets for each method, in order to enable readers to try it easily.
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@KirkDBorne: “12 Statistical & #MachineLearning Methods Every #DataScientist Should Know: #DataScience”
Below is my personal list of statistical and machine learning methods that every data scientist should know in 2016.
Statistical Hypothesis Testing (t-test, c…
12 Statistical and Machine Learning Methods that Every Data Scientist Should Know