Get the latest machine learning algorithms and techniques
Are you looking for a Data Science easy button? The dataSciencePilot action set comes pretty close.
Are you looking for a Data Science easy button? The Data Science Pilot Action Set comes pretty close.
Validating and testing our supervised machine learning models is essential to ensuring that they generalize well. SAS Viya makes it easy to train, validate, and test our machine learning models.
Neural networks, particularly convolutional neural networks, have become more and more popular in the field of computer vision. What are convolutional neural networks and what are they used for?
Learn how Bayesian optimization works through a simple demo.
What is object detection? Object detection, a subset of computer vision, is an automated method for locating interesting objects in an image with respect to the background. For example, Figure 1 shows two images with objects in the foreground. There is a bird in the left image, while there is a dog
We have updated our software for improved interpretability since this post was written. For the latest on this topic, read our new series on model-agnostic interpretability. While some machine learning models – like decision trees – are transparent, the majority of models used today – like deep neural networks, random forests, gradient boosting
There are four widely recognized styles of machine learning: supervised, unsupervised, semi-supervised and reinforcement learning. These styles have been discussed in great depth in the literature and are included in most introductory lectures on machine learning algorithms. As a recap, the table below summarizes these styles. For a comprehensive mapping
Deep learning has taken off because organizations of all sizes are capturing a greater variety of data and can mine bigger data, including unstructured data. It’s not just large companies like Amazon, SAS and Google that have access to big data. It’s everywhere. Deep learning needs big data, and now
In machine learning, a feature is another word for an attribute or input, or an independent variable. What is feature engineering? Feature engineering is a process of preparing inputs for machine learning models. The goal of feature engineering is to to improve classification accuracy by considering the limitations of the
