The world of data science is awash in open source: PyTorch, TensorFlow, Python, R, and much more. But the most widely used tool in data science isn’t open source, and it’s usually not even ...

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.

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 ...

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 ...

Data science and machine learning professionals have driven adoption of the Python programming language, but data science and machine learning are still lacking key tools in business and has room ...

Welcome to the Data Science course! Over the next 50 days, you will learn a wide range of topics related to Python programming, data science, and machine learning. These topics will be covered in a ...

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 ...