What is the next step?
Overview
Teaching: 10 min
Exercises: 0 minQuestions
What do I do now?
What is the next step?
Objectives
Present suggestions for further reading,
Tips on problems to work on to practice,
What should I do next?
Great data
First of all: If you do not have data you want to work with already. Find some!
Kaggle host competitions in machine learning. For the use of those competitions, they give access to a lot of interesting datasets to work with. With more than 200.000 datasets at time of writing, it can be a bit overwhelming, so consider looking at the “datasets” available as CSV-files.
Great books
Many exists, some are available online, some are even free!
Our favorite is R for Data Science by Hadley Wickham and Garrett Grolemund. The https://r4ds.hadley.nz/ is coming soon. Both editions have a chapter on Exploratory Data Analysis.
Great sites
Most of the larger sites offering online courses in “something-with-data” offers courses that can support your learning in regards to exploratory data analysis:
Contact us!
The whole reason for the existence of KUB Datalab is to help and assist students (and teachers and researchers) working with data.
We do not guarantee that we will be able to solve your problems, but we will do our best to help you.
Our calender, containing our activities, courses, seminars, datasprints etc.
Our website
Our mail: kubdatalab@kb.dk
Key Points
Practice is important!
Working on data that YOU find interesting is a really good idea,
The amount of ressources online is immense.
KUB Datalab is there for your.