Subject

Data

Why the buzz around GNNs?

From Graph Neural Networks in Action by Keita Broadwater

Building and Using Topologies

From PostGIS in Action, Third Edition by Leo S. Hsu and Regina O. Obe

In this article, you’ll learn what a topology is, how to build a topology from scratch, and how to use commonly available geometry data.

Managing Data Sources in Machine Learning

From Graph-Powered Machine Learning by Alessandro Negro

This article discusses managing data in graph-powered machine learning projects.

Getting to Know GPUs

From Parallel and High-Performance Computing by Robert Robey and Yuliana Zamora

This article takes a deep dive into GPUs.

Deploying Machine Learning Models, Part 5: deployment

In this series, we cover model deployment: the process of putting models to use. In particular, we’ll see how to package a model inside a web service, allowing other services to use it. We also show how to deploy the web service to a production-ready environment.

Creating a Bipartite Graph for a User-Item Dataset

By Graph-Powered Machine Learning Alessandro Negro

This article discusses creating a bigraph for a user-item dataset.

Computing Travel Probabilities Using Matrix Multiplication

From Data Science Bookcamp by Leonard Apeltsin

This article discusses how to model a traffic simulation and compute travel probability.

Deploying Machine Learning Models, Part 4: creating a Docker image

From Machine Learning Bookcamp by Alexey Grigorev

In this series, we cover model deployment: the process of putting models to use. In particular, we’ll see how to package a model inside a web service, allowing other services to use it. We also show how to deploy the web service to a production-ready environment.

Deploying Machine Learning Models, Part 3: managing dependencies

From Machine Learning Bookcamp by Alexey Grigorev In this series, we cover model deployment: the process of putting models to use. In particular, we’ll see how to package a model inside a web service, allowing other services to use it…. Continue Reading →

Setting Limits on Experimentation

This article talks about the need to carefully plan a machine learning project—before you start it!

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