Technology|Jun 24, 2021

Non-Technical Priorities for App Migrations into Azure

Migrations to another environment can be trivial for some applications, but it’s a complex array of different parts that all work together for most of them. Migrating such applications is a complex task of analysis and decision-making oriented around many different factors. Most application migrations to Azure begin with prework that performs business analysis on…
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AI|Jun 22, 2021

ML & AI for Software Developers - Part 8
Binary Classification: Spam Filtering

My previous post introduced a machine-learning model that used logistic regression to predict whether text input to it expresses positive or negative sentiment. We used the probability that the text expresses positive sentiment as a sentiment score, and saw that expressions such as “The long lines and poor customer service really turned me off” score…
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Webinar|Jun 17, 2021

Different Paths for Migrating Apps to Azure

There are multiple ways to host applications on Azure, each with its pro’s and cons. In this webinar, we’ll look at three different possibilities between Azure App Services, Azure infrastructures, and lastly at containers, then weight the pros and cons of each of these when moving into Azure.
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Webinar|Jun 3, 2021

Microservices On Azure: Containers, Serverless, and Everything Else

Microservices provide a great way to build scalable, manageable, and available applications across vast regions. Especially for newer suites, choosing the right technology to support microservices has its advantages and tradeoffs to make things simpler or more flexible. In this webinar, you will learn how the different technologies impact microservices to help you make better-informed…
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AI|May 27, 2021

ML & AI for Software Developers - Part 6
Binary Classification

The machine-learning model featured in my previous post was a regression model that predicted taxi fares based on distance traveled, the day of the week, and the time of day. Now it’s time to tackle classification models, which predict categorical outcomes such as what type of flower a set of measurements represent or whether a…
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Blogs|May 21, 2021

Azure Migrations - Part 3
App Services Migration Assistant Assessment Report

Azure App Services is a popular choice for migrating apps to Azure because it gets users out of the business of managing servers. But with App Services, some limitations might mean reconfiguring or refactoring an application. The Migration Assistant utility can provide a quick report that shows you things you need to consider before moving…
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Webinar|May 20, 2021

Introduction to Azure Databricks

Data volumes are increasing rapidly and with it, insights can be gained at cloud scales. Azure Databricks enables developers to leverage the combined power of Azure, Delta Lake, and Apache Spark to utilize structured and unstructured data for insights, real-time feedback, and application development. In this session, you’ll learn the basics of Azure Databricks, the…
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AI|May 19, 2021

ML & AI for Software Developers - Part 5
Regression Modeling

When you build a machine-learning model, the first and most important decision you make is what learning algorithm to use to fit the model to the training data. In my previous post, I introduced some of the most widely used learning algorithms for regression models: linear regression, decision trees, random forests, gradient-boosting machines (GBMs), and…
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Webinar|May 13, 2021

Making the Most of Microservices

Microservices offer a way to create hyper scale applications that can meet the demands of even the most challenging workloads. But with microservices, come with their own sets of challenges that have to be solved. In this webinar, we look at these challenges: state, configuration management, service discovery, interservice communication, security, and scaling data. With…
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Azure and Cloud Computing|May 7, 2021

Azure Migrations - Part 2
Starting an Assessment with Discovery

The first critical step in migrating anything to Azure is an assessment of what we want to move. The assessment starts with a discovery wherein various aspects of a workload are teased out to expose what composes and supports the workload. These include business drivers, governance drivers, security, and the actual workload itself. In this…
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AI|May 6, 2021

ML & AI for Software Developers - Part 4
Regression Algorithms

Supervised-learning models come in two varieties: regression models and classification models. Regression models predict numeric outcomes, such as the price of a car. Classification models predict classes, such as the breed of a dog in a photo. When you build a machine-learning model, the first and most important decision you make is what learning algorithm…
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