An excerpt from Julia for Data Analysis by Bogumil Kaminski
This article dives into working with data in dataframes with Julia.
Read it if you’re a data scientist or anyone who works with lots of data, and if you’re interested in the Julia language.
An excerpt from Julia for Data Analysis by Bogumil Kaminski
Many languages designed for doing data science provide ways to perform vectorized operations, which is also often called broadcasting. In Julia, broadcasting is also supported. In this article you will see how to use it.
Read it if you’re a data scientist or anyone who works with lots of data, and if you’re interested in the Julia language.
From Learn PowerShell in a Month of Lunches, 4th Edition by Travis Plunk, James Petty, Tyler Leonhardt, Don Jones, Jeffery Hicks
An excerpt from Julia for Data Analysis by Bogumil Kaminski
This article shows you how to use Multiple Dispatch in Julia.
Read it if you’re a data scientist or anyone who works with lots of data, and if you’re interested in the Julia language.
From Distributed Machine Learning Patterns by Yuan Tang
In this article, we introduce the collective communication pattern, which is a great alternative to parameter servers when the machine learning model we are building is not too large without having to tune the ratio between the number of workers and parameter servers.
From Distributed Machine Learning Patterns by Yuan Tang
In this article, we introduce the parameter server pattern which comes handy for situations where the model is too large to fit in a single machine such as one we would have to build for tagging entities in the 8 millions of YouTube videos.
From GitOps and Kubernetes by Billy Yuen, Alexander Matyushentsev, Todd Ekenstam, and Jesse Suen
This article delves into Canary deployments: what they are; how they work; and where you might consider using them.
From GitOps and Kubernetes by Billy Yuen, Alexander Matyushentsev, Todd Ekenstam, and Jesse Suen
