In this article, we shall see how the Bayesian Kalman Filter can be used to predict positions of some moving particles / objects in 2D.
This article is inspired by a programming assignment from the coursera course Robotics Learning by University of Pennsylvania, where the goal was to implement a Kalman filter for ball tracking in 2D space. Some part of the problem description is taken from the assignment description.
Added by Sandipan Dey on August 31, 2017 at 12:30pm — No Comments
Given a set of labeled images of cats and dogs, a machine learning model is to be learnt and later it is to be used to classify a set of new images as cats or dogs.
The following problems appeared in the assignments in the Udacity course Deep Learning (by Google). The descriptions of the problems are taken from the assignments (continued from the last post).
Here is how some sample images from the dataset look like:
Let’s try to get the best performance using a multi-layer model!…Continue
Added by Sandipan Dey on August 3, 2017 at 10:30pm — No Comments
Added by Sandipan Dey on August 1, 2017 at 1:30am — No Comments