Beyond “def”: Exploring Python Functions

In this tour de force live coding session, an expert Python coach Reuven Lerner shows you how functions work behind the scenes and how you can use them in different ways.

What Are Web APIs?

From Developing Microservice APIs with Python by Jose Haro Peralta

In this article we will explain what web APIs are. You will learn that a web API is a specific instance of the more general concept of Application Programming Interface (API). It is important to understand that an API is just a layer on top of an application, and that there are many different types of interfaces.

Function Pipelines for Mapping Complex Transformations

From Mastering Large Datasets with Python by J.T. Wolohan

This article covers

· Using map to do complex data transformations

· Chaining together small functions into pipelines

· Applying these pipelines in parallel on large datasets

Neural Network Architectures

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

This article dives into neural network architectures and how get started implementing and using them.

Working with Large Datasets Faster: using the map function

From Mastering Large Datasets by JT Wolohan

This article explores using the map function creatively in a data project.

Modern Data Solutions with Python

From Mastering Large Datasets with Python by John T. Wolohan




Building Linear Models with Dask ML

From Data Science at Scale with Python and Dask by Jesse C. Daniel

This article delves into building linear models using Dask-ML.

Learn Coding Best Practices in Python

From Practices of the Python Pro by Dane Hillard


The Towers of Hanoi

Six Questions for David Kopec, author of Classic Computer Science Problems in Python

David Kopec is Assistant Professor in computer science at Vermont’s Champlain College and author of two books in the Classic Problems series. If you want more, find @davekopec on Twitter.

Constraint-Satisfaction Problems in Python

From Classic Computer Science Problems in Python by David Kopec

A large number of problems which computational tools solve can be broadly categorized as constraint-satisfaction problems (CSPs). CSPs are composed of variables with possible values which fall into ranges known as domains. Constraints between the variables must be satisfied in order for constraint-satisfaction problems to be solved. Those three core concepts—variables, domains, and constraints—are simple to understand, and their generality underlies the wide applicabilit

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