Why do data scientists and data engineers work with synthetic data? How do they obtain it? Discover Trumania, a scenario-based random dataset generator library.
importing & cleaning data+2
Discover active learning, a case of semi-supervised machine learning: from its definition and its benefits, to applications and modern research into it.
Learn about Python tuples: what they are, how to create them, when to use them, what operations you perform on them and various functions you should know.
Learn to set up a data science environment on Google Cloud: create an instance on Google Compute Engine, install Anaconda and run Jupyter notebooks!
Applying matrix factorization on user clicks on hundreds of names on the recommender system NamesILike.com reveal an unseen structure in our first names.
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.