Python has become the lingua franca of data science and is, therefore ... This notebook will discuss different techniques for grouping data, including binning, one-hot encoding, and clustering. We ...

Already using NumPy, Pandas, and Scikit-learn? Here are five more powerful Python data science tools that deserve a place in your toolkit. Python’s rich ecosystem of data science tools is a big ...

van Lith and Joaquin Vanschoren provide a framework titled “From string to Data Science” for systematically identifying and encoding various sorts of categorical string features in tabular datasets.

Using a mixture of Python, R, and common command-line tools, Cleaning Data for Effective Data Science follows the data cleaning pipeline from start to end, focusing on helping you understand the ...

This online data science specialization is designed for learners with little to no programming experience who want to use Python as a tool to play with data. You will learn basic input and output ...

A new offering from the creator of a Python distribution for data science uses Microsoft Excel as a front end for Jupyter notebooks and other data-centric apps Some of the most creative uses for ...

More generally, Haskell excels at abstraction, and data science benefits from coherent ... Haskell is great for encoding the complex and sometimes arbitrary business rules our operations follow.

But data science is a specific field, so while Python is emerging as the most popular language in the world, R still has its place and has advantages for those doing data analysis. Hoping to ...

Netflix's data-science team has open-sourced its Metaflow Python library, a key part of the 'human-centered' machine-learning infrastructure it uses for building and deploying data-science workflows.