Subject

Data Science

The Computer Vision Pipeline, Part 4: feature extraction

From Deep Learning for Vision Systems by Mohamed Elgendy

In this part, we will take a look at feature extraction—a core component of the computer vision pipeline.

Combining Human and Machine Intelligence

From Human-in-the-Loop Machine Learning by Robert Munro


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Maximise Customer Retention

From Fighting Churn with Data by Carl Gold


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Is my Problem a Graph Problem?

From Graph Databases in Action by Dave Bechberger

In this article, we’ll review what makes a problem a good graph use case. We’ll start by examining a few general categories of problems and discussing why they might make for good graph use case.  Finally, we’ll analyze a general framework that we can use to help us decide if our problem is a good graph use case.

The Computer Vision Pipeline, Part 3: image preprocessing

From Deep Learning for Vision Systems by Mohamed Elgendy

In this part, we will delve into image preprocessing for computer vision systems.

The Data Scientist’s Survival Guide

From Build Your Career in Data Science by Emily Robinson and Jacqueline Nolis


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Want to Learn Machine Learning Inside Out?

From Grokking Machine Learning by Luis G. Serrano


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Fun & Games

Six Questions for Kevin Ferguson, co-author of Deep Learning and the Game of Go.

Kevin Ferguson and Max Pumperla are deep learning specialists skilled in distributed systems and data science. Together, they built the open source bot BetaGo. They also both count Max, the hero of the movie Pi, as a major influence. “He’s a talented mathematician who slowly loses his mind over the stock market and has an intense relationship with his power tools. That’s essentially my short bio,” says Pumperla.

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.

Computer Vision Pipeline, Part 1: the big picture

From Deep Learning for Vision Systems by Mohamed Elgendy

In this article, we’ll zoom in on the interpreting device component (of a computer vision system) to take a look at the pipeline it uses to process and understand images.

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