In this blog post you will learn what machine vision is and how a model can be trained to detect objects in images. Machine vision or computer vision is the field of making machines see and detect objects within images and videos with a certain confidence level.
When designing the architecture for an artificial neural network, there exist a variety of parameters that can be tuned. It is indeed an art in itself to find the right combination for these parameters to achieve the highest accuracy and lowest loss. In this blog post, we are testing the usage of Talos for hyperparameter optimization of a neural network.
In previous blog post about Credit Card Fraud we used an artificial neural network for predicting whether a given transaction is fraudulent, with great results. However, sometimes in problems like these, where we naturally have an imbalanced distribution in our dataset, we might not always have collected data for the minority of the outcomes, in this case, the fraudulent transactions.
Artificial Intelligence (AI) is a hot topic! Many companies are currently considering how they can use AI to improve their businesses, new CXO titles such as Chief Data Officer and Data Privacy Officer is starting to see use. Furthermore, people start to consider what their data is being used for and want to know how AI will affect their daily lives.
Following blogpost is aiming towards the healthcare industry, with the objective to enlighten how machine learning can automate processes, and thereby reduce workload for nurses and doctors. A case will be shown on predicting whether a given tumor in the breast is malignant or benign, but could as well be a picture from a X-ray detecting whether a bone is broken or not.
Unplanned downtime is costly in many aspects within manufacturing. It reduces delivery capability, customer satisfaction, and increases overall costs. So which maintenance approach should we use to reduce the frequency of downtime?
The following blog post is a continuation of Showdown of artificial neural networks and support vector machines where we validated the quality of red wine, with a neural network and support vector machine. This time, we will show what efforts go into making a support vector machine model production ready!