From Practices of the Python Pro by Dane Hillard
This article covers
• Recognizing the signs of tightly coupled code
• Strategies for reducing coupling
From PySpark in Action by Jonathan Rioux
From Practices of the Python Pro by Dane Hillard
This article covers
From Data Science Bookcamp by Leonard Apeltsin
From Practices of the Python Pro by Dane Hillard
The article explores the concept of namespaces and how Python uses them to help make code better.
From Zero to AI by Nicolo Valigi and Gianluca Mauro
Six Questions for Jesse C. Daniel, author of Data Science with Python and Dask
Jesse Daniel is a software developer (Python, Scala, JavaScript, C#) who leads a team of data scientists at a media technology company. He has taught Python for Data Science at the University of Denver.
From Practical Data Science with R, Second Edition by Nina Zumel and John Mount
This article discusses how one can experiment with the effectiveness of a classification model using a spam filter.
From Azure Storage, Streaming, and Batch Analytics by Richard Nuckolls
This article delves into Azure’s tools for data engineering and why you should consider using them.