A Walk in the Tidyverse
If you worked with R to explore a dataset and build a report from this analysis, you have probably heard about the tidyverse. If you used R in your data science project, to fit a predictive model able to produce the most accurate prediction possible for... Read more
MLOps V2 Solution Accelerator – Unifying MLOps at Microsoft
MLOps means different things to different people, however, the fundamental essence of MLOps is to deliver models into productions faster with a consistent, repeatable, and reliable approach. Machine Learning Operations (MLOps) is key to accelerating how data scientists and ML engineers can impact organizational needs. A... Read more
Many Models Training with Hyperparameter Optimization
This article presents an approach for you to train multiple machine learning models, optimizing the hyperparameters of each model in an automated way with Azure Machine Learning. Before getting into the part where I explain how to do this, let’s first get a better understanding of... Read more
How to Choose the Best GPU Optimized VM Sizes for Your Project on Azure
A common problem that data scientists face when training and deploying their machine learning models is the choice of the right type and size of hardware. Migrating machine learning tasks on the Cloud significantly simplified the data scientist’s job, who now just needs to login into... Read more
How a Neural Network Sees a Cat
As human beings, we know what a cat looks like. But what about neural networks? In this post, we reveal what a cat looks like inside a neural network brain, and also talk about adversarial attacks. Real and Ideal cat. Image on the left is from Unsplash... Read more
Azure Machine Learning CLI v2 and Python SDK v2
Azure Machine Learning is committed to simplifying the adoption of its platform for training and production cycles. Over the last several months, we have worked on adding support for workflows using command lines and support for scripts in multiple languages. We have also worked on bringing... Read more
AI Gets Bigger and Better: Microsoft’s AI-at-Scale Predictions
Two years ago, when Luis Vargas, Ph.D. of Microsoft AI addressed ODSC, he told the story of his daughter learning multiple languages as a small child and how this hidden complexity transferred to teaching machines to learn. The development of AI follows a similar path as... Read more
AIOps with Azure Metrics Advisor
AIOps is a term introduced by Gartner in 2016, referring to AI for IT Operations. It combines big data and machine learning to automate IT operations processes, including event correlation, anomaly detection, and causality determination. As more companies adopt digital transformation initiatives, we are seeing an explosion... Read more
Extracting Information From Unstructured Documents with Azure Form Recognizer
Extracting information from unstructured documents such as contracts is usually manual and involves tediously reading and understanding substantial amounts of documents to find specific information and manually extracting the information to digitize it. The process consumes a significant amount of a lawyer’s billable hours and is... Read more
Creating Managed Online Endpoints in Azure ML
Suppose you’ve trained a machine learning model to accomplish some task, and you’d now like to provide that model’s inference capabilities as a service. Maybe you’re writing an application of your own that will rely on this service, or perhaps you want to make the service... Read more