Getting the Power of Spark to Your Data Engineers
Over the last decade, there has been a giant leap in the technology available to the market for processing big data workloads.
Deep Learning
Deep learning is a subset of machine learning that relies primarily on neural networks. Most of what’s considered AI today is accomplished with deep learning. From recognizing objects in photos […]
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 […]
Using GitHub Actions to Manage Certbot (Let’s Encrypt) Certificates
GitHub Actions is an excellent source for all things automation. For personal accounts, there’s a limited free offering that allows you to run automation jobs. I use GH actions to […]
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.
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 […]
Operationalizing Machine-Learning Models
All of the machine-learning models presented so far in this series were written in Python. Models don’t have to be written in Python, but many are, thanks in part to […]
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 […]
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 […]