Azure Databricks Series - Part 1
Intro to Azure Databricks

Many companies today have aging data architectures. As you look to modernize your traditional ETL pipeline, there is a tool you should keep in mind: Azure Databricks. During your move into Azure, there will probably be a place for Azure Databricks. In the past, general DTS/SSIS pipelines and SQL Server engines were sufficient but with…

ML & AI for Software Developers - Part 15
Building Machine-Learning Models with ML.NET

Scikit-learn is arguably the world’s most popular machine-learning framework. The efficacy of the library, the documentation that accompanies it, and the mindshare that surrounds it are the primary reasons more ML models are written in Python than any other language. But Scikit isn’t the only machine-learning framework. Others exist for other languages, and if you…

Azure Migrations - Part 4
Database Migration Assistant Assessment

Azure offers a lot of options for moving SQL databases from SQL Server to Azure. Knowing which choice is the best choice for your database can sometimes be challenging. Microsoft provides a tool, the Database Migration Assistant, that assesses your database to show you if it is compatible or not. And what changes you may…

AI and ML Embedded in Azure Data Platform

You can deploy AI/ML solutions in multiple places: IoT devices, at the cloud edge, and in cloud API endpoints, among other locations. In this session, learn the options available in Azure Data Platform services and how they can improve transactional systems in the back end. We will also walk through some business intelligence (BI) use…

ML & AI for Software Developers - Part 13
Recommender Systems

Another branch of machine learning that has proven its mettle in recent years is recommender systems – systems that recommend products or services to customers. Amazon’s recommender system reportedly drives 35% of its sales. The good news is that you don’t have to be Amazon to benefit from a recommender system, nor do you have…

ML & AI for Software Developers - Part 12
PCA-Based Anomaly Detection

Anomaly detection is a branch of machine learning that seeks to identify anomalies in datasets or data streams. Airbus uses it to predict failures in jet engines and detect anomalies in telemetry data beamed down from the International Space Station. Credit-card companies use it to detect credit-card fraud. The goal of anomaly detection is to…

ML & AI for Software Developers - Part 11
Principal Component Analysis

Principal Component Analysis, or PCA, is one of the minor miracles of machine learning. It’s a dimensionality-reduction technique that reduces the number of dimensions in a dataset without sacrificing a commensurate amount of information. While that might seem underwhelming on the face of it, it has profound implications for engineers and software developers working to…

ML & AI for Software Developers - Part 10
Support-Vector Machines

Support-vector machines, also known as SVMs, represent the cutting edge of statistical machine learning. They are typically used for classification problems, although they can be used for regression, too. SVMs often succeed at finding separation between classes when other models – that is, other learning algorithms – do not. Scikit-learn makes building SVMs easy with…

Moving to ASP.NET Core: Replacing HTML Helpers that have Dependencies

Moving to ASP.NET Core: Replacing HTML Helpers that have Dependencies The HTML Helper is born To make it easier to add content to a view, you can take advantage of something called an HTML Helper. You can use HTML Helpers to generate standard HTML elements such as textboxes, links, dropdown lists, and list boxes. They…
Windows 11

Windows 11 — Initial Reactions and Thoughts

Windows 11 made a big splash with the announcement of the new version of the OS that was supposed to never have another version again. In any case, as part of the Windows Insider Program (WIP), I got my hands on the latest preview version of the OS, installed it, and poked around in it…

ML & AI for Software Developers - Part 9
Multiclass Classification

The three previous posts in this series introduced binary classification and provided working examples of its use, including sentiment analysis and spam filtering. Now it’s time to tackle multiclass classification, in which there are n possible outcomes rather than just two. A great example of multiclass classification is performing optical character recognition: examining a hand-written…