In this post you will learn how to build a simple neural network using Tensorflow!
We continue our journey through neural networks and we explore the training stage, when gradient descent allows us to select optimal parameters for the ANN.
This posts introduces the basic concepts about artificial neural networks (ANN).
In the previous two posts we saw how to use Scikit Image to perform some basic image processing. This post will introduce you to image segmentation, one of the most important steps in image analysis. I am going to cover some of the “traditional” methods that work well in many situations. These methods require adaptation […]
In the first part of this series, we looked at how to open images and perform some basic manipulations using Scikit Image. This second part will introduce you to digital image filters! Digital filters for image analysis Often we need to perform some operation on our images. For example, we may want to reduce noise, […]
This post introduces Scikit Image, as a great tool to create automated pipelines for image analysis. In this part, I cover some basic operations such as cropping and histogram manipulation.
Introduction In previous posts, I discussed how to deal with situations where you measure a continuous outcome and you want to explain its variability as a function of one or more continuous or discrete variables, using linear regression or mixed-effects models. However, there are situations where these linear models are not the best solution to […]
Pseudoreplication is a major issue in biomedical sciences. This post will show you how to avoid it and properly analyse your data in R!
Binary trees are a simple, yet powerful machine learning tool used for classification. In this post, we will use them to classify images of breast cancer.
This post will introduce you to ggplot, an R package which makes it super-easy to create visually pleasing plots with just a few lines of code!