Machine Learning is a broad field in which we can distinguish different types of algorithms. One of them is unsupervised learning, where the learning data is unlabelled. Today I would like to introduce you to K-Means Clustering which is part of unsupervised algorithms that is used to solve clustering...
Image by Colin Behrens from Pixabay As you can know or see according to my other posts, I enjoy exploring and learning new things about Machine Learning and Artificial Intelligence. One aspect that I am investigating is creating ML algorithms in the .NET environment. So far I have used...
Microsoft Azure contains many various services. One of them is a service that allows speech translation, which is part of Cognitive Services. How does it work? What is it about? How to use it in your application? In this blog post, I will try to answer these questions and...
More and more has been saying recently about the concept of no code. It is a platform for building applications without coding. You can create software and configure everything using just the mouse, a perfect way for non-technical people. ML.NET Model Builder can be described as a small seed...
Transfer Learning is a popular tool in the field of Deep Learning. It is used to reuse a previously created model for a new problem. Thanks to that you can train neural networks with little data, which significantly saves time and memory resources required. This type of algorithm is...
I already introduced you to Adaptive Boosting Classifier and Gradient Boosting Classifier, so now it is time to go to another ensemble classifier which I used in my research during creating a master’s thesis – Stacking. It will be a theoretical introduction to this algorithm and an example of...
I graduated in Computer Science a few days ago, so now I have finally time to writing again here. Some time ago I wrote an article about Adaptive Boosting Classifier. Today I would like to introduce you to another ensemble classifier – Gradient Boosting Classifier. Here we are dealing...
I am just finishing writing my master’s thesis, whose subject is recognizing epileptic states based on the EEG signal using the ensemble classifiers. One of the ensemble classifiers that I used in my research was Adaptive Boosting Classifier. I decided to write an article about it. This will be...
If you have some experience in machine learning and have evaluated the results of some classifications, you have certainly used metrics such as accuracy, precision or f1-score. However, there are also other, less popular metrics that are worth using. One of them is cohen’s kappa. Today I want to...
The process of creating a model for a given machine learning problem is not only based on throwing all available features from the dataset into the algorithm. It is good practice to check what particular features affect the target variable and create a feature ranking, which is one of...
