In this post we will explore a class of machine learning methods called Support Vector Machines also known commonly as SVM.
Tree based learning algorithms are quite common in data science competitions. These algorithms empower predictive models with high accuracy, stability and ease of interpretation. Unlike linear models, they map non-linear relationships quite well. Common examples of tree based models are: decision trees, random forest, and boosted trees.
Lately, a lot of my friends have been asking about my deep learning workstation setup. In this post I am going to describe my hardware, OS, and different packages that I use. In particular, based on the question, I found that the most of the interest have been around managing different python versions, and modules like pytorch/tensorflow libraries etc.
Object detection is useful for understanding what’s in an image, describing both what is in an image and where those objects are found. In general, there are two different approaches for this task –