Tag

data science

What Makes Code Extensible and Flexible?

From Practices of the Python Pro by Dane Hillard

This article covers

  • Using inversion of control to make code flexible
  • Using interfaces to make code extensible
  • Adding new features to your existing code

Improve Your Data Science Skills

From Data Science Bookcamp by Leonard Apeltsin

Namespacing with Python

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.

Zero to AI

From Zero to AI by Nicolo Valigi and Gianluca Mauro

Data Science and Bucatini all’Amatriciana

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.

Evaluating a Classification Model with a Spam Filter

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.

Why Choose Azure for Data Engineering?

From Azure Data Engineering by Richard Nuckolls

This article delves into Azure’s tools for data engineering and why you should consider using them.

A New Approach to Deep Learning

From Probabilistic Deep Learning with Python by Oliver Dürr, Beate Sick, and Elvis Murina


slideshare-a-new-approach-to-deep-learning

The Computer Vision Pipeline, Part 5: Classifier learning algorithms and conclusion

From Deep Learning for Vision Systems by Mohamed Elgendy

Basic Time-Series Forecasting

From Machine Learning for Business by Doug Hudgeon and Richard Nichol

This article covers basic time-series forecasting: what it is and why it’s a tough problem.

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