Learn all about the Python iterator, how they differ from iterables and generators, and how to build one yourself with __iter__, __next__ and itertools.
In this tutorial, you’ll see what transfer learning is, what some of its applications are and why it is critical skill as a data scientist.
Which shell commands do data scientists use nearly every day? Discover and learn how to use them in this tutorial!
Learn how to build your first machine learning model, a decision tree classifier, with the Python scikit-learn package, submit it to Kaggle and see how it performs!
Five useful tips that you can use to effectively improve your R code, from using seq() to create sequences to ditching which() and much more!
Learn all about Python dictionary comprehension: how you can use it to create dictionaries, to replace (nested) for loops or lambda functions with map(), filter() and reduce(), ...!
Get introduced to Python data structures: learn more about data types and primitive as well as non-primitive data structures, such as strings, lists, stacks, etc.