Category: Blogs

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 […]

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.

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 […]

Supervised Learning with k-Nearest Neighbors

Most machine-learning models fall into one of two categories. Supervised-learning models make predictions. For example, they predict whether a credit-card transaction is fraudulent or a flight will arrive on time. […]

Unsupervised Learning with k-Means Clustering – Part II

Machine-learning models fall into two broad categories: supervised-learning models and unsupervised-learning models. The purpose of supervised learning is to make predictions. The purpose of unsupervised learning is to glean insights […]

Machine Learning and AI for Software Developers

Machine learning (ML) and artificial intelligence (AI) are transforming the way software is written and, more importantly, what software is capable of. Developers are accustomed to writing code that solves […]

Atmosera is thrilled to announce that we have been named GitHub AI Partner of the Year.

X