In this video, we join Nuwan Dias in securing service-to-service interactions over gRPS and Kafka.
In this video, machine learning expert Eli Stevens showcases how to use open-source libraries that are available in the PyTorch ecosystem to cut down the amount of the code that you want to write.
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.
From Machine Learning with TensorFlow, Second Edition by Chris Mattmann This article covers: Building sentiment classifier using logistic regression and with softmax Measuring classification accuracy Computing ROC curve and measure classifier effectiveness Submitting your results to the Kaggle challenge for… Continue Reading →
By Vlad Riscutia
This is an excerpt from chapter 2 of my book — Data Engineering on Azure — which deals with storage. In this article we’ll look at a few aspects of data ingestion: frequency and load type, and how we can handle corrupted data. We’ll use Azure Data Explorer as the storage solution, but keep in mind that the same concepts apply regardless of the data fabric used. Code samples are omitted from this article, but are available in the book. Let’s start by looking at the frequency with which we ingest data.
From Functional Programming in Kotlin by Marco Vermeulen, Rúnar Bjarnason, and Paul Chiusano
This article covers how monads, monad combinators, and functors work and why you should be afraid of them.
Graphs and network science: An Introduction is a free eBook with chapters selected by Tomaz Bratanic.