Tag

python

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 Code Like a Pro by Dane Hillard

slideshare-learn-coding-best-practices-in-python

The Towers of Hanoi: six questions with David Kopec

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

By Frances Lefkowitz

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

Free eBook: Exploring Python Basics

Free-eBook-Ceder_EPB

Chapters selected by Naomi Ceder

Thinking in Python: six questions with Naomi Ceder

Naomi Ceder, author of The Quick Python Book, Third Edition

By Frances Lefkowitz, Development Editor, Manning Publications

Naomi Ceder earned a Ph.D in Classics, but, since 2001, has been learning, teaching, and using Python. An elected fellow of the Python Software Foundation, Naomi currently serves as chair of its board of directors. She also speaks internationally about the Python community, and on inclusion and diversity in technology in general. By day she leads a team of Python programmers for Dick Blick Art Materials, and in her spare time she enjoys sketching, knitting, and deep philosophical conversations with her dog.

PyTorch Crash Course, Part 3

From Deep Learning with PyTorch

by Eli Stevens and Luca Antiga

In this article, we explore some of PyTorch’s capabilities by playing generative adversarial networks.

What do Cooking Pasta and Data Science Have in Common?

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

This article discusses Dask, how it compares to Apache Spark, and how to create and understand directed acyclic graphs using the example of the delicious Italian pasta dish bucatini all’Amatriciana.

PyTorch Crash Course, Part 2

From Deep Learning with PyTorch by Eli Stevens and Luca Antiga

In this article, we explore some of PyTorch’s capabilities by playing with pre-trained networks.

Learn to Program!


slideshare-learn-to-program

From Get Programming with Python in Motion
By Ana Bell

© 2019 Manning — Design Credits