Tag

algorithms

Data Compression with Huffman’s Algorithm

From Algorithms and Data Structures in Action by Marcello La Rocca

This article discusses Huffman’s Algorithm: what it is and what you can do with it.

Packing Your Knapsack for a Trip to Mars

From Algorithms and Data Structures in Action by Marcello La Rocca

You’ve been selected to be among the first people to colonize Mars! Now you have to pack the optimal amount of food to get the most calories per kilogram—how can algorithms help?

Expand Your Programming Skill Set

From Algorithms and Data Structures in Action by Marcello La Rocca


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The Computer Vision Pipeline, Part 2: input images

From Deep Learning for Vision Systems by Mohamed Elgendy

In this part, we will discuss the input images for computer vision systems.

The Random Cut Forest Algorithm

From Machine Learning for Business by Doug Hudgeon and Richard Nichol

In this article, you’ll see how SageMaker and the Random Cut Forest algorithm can be used to create a model that will highlight the invoice lines that Brett should query with the law firm. The result will be a repeatable process that Brett can apply to every invoice that will keep the lawyers working for his bank on their toes and will save the bank hundreds of thousands of dollars per year. Off we go!

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.

Anticipating your Opponent with Minimax Search

From Deep Learning and the Game of Go by Max Pumperla and Kevin Ferguson

This article shows you how to use the minimax algorithm to help your game bot decide its next move.

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

Learn the Math You Need for Today’s Hottest Careers!

From Math for Programmers by Paul Orland

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Learning Computer Science with Python

From Classic Computer Science Problems in Python by David Kopec


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