### Understanding Data Parallelism in Machine Learning

In this post, I’ll show how to modify the spiral data set example presented in Karpathy’s post (http://cs231n.github.io/neural-networks-case-study/) to run in a data parallel mode. […]

In this post, I’ll show how to modify the spiral data set example presented in Karpathy’s post (http://cs231n.github.io/neural-networks-case-study/) to run in a data parallel mode. […]

The purpose of this post is to provide some additional insights and Matlab and CNTK implementations for the two layer network used to classify a […]

Over the last month, I have been exploring the world of deep learning. Deep learning based algorithms have been around for a long time, but […]

We are all familiar with GPS (Global Positioning System) and its myriad applications. From getting directions using Google maps to hailing a ride using a ride sharing […]

In this post, we’ll add the math and provide implementation for adding image based measurements. Let’s recap the notation and geometry first introduced in part […]

In the previous posts, we laid the mathematical foundation necessary for implementing the error state kalman filter. In this post, we’ll provide the Matlab implementation […]

In the previous post, we laid some of the mathematical foundation behind the kalman filter. In this post, we’ll look at our first concrete example […]

In this series of posts, I’ll provide the mathematical derivations, implementation details and my own insights for the sensor fusion algorithm described in 1. This paper describes a […]

In this post, I’ll describe the lessons learnt from trying to sample IMU sensors to obtain raw gyroscope and accelerometer data as input to sensor […]

In the last post, we applied bundle adjustment to optimize camera intrinsic and extrinsic parameters keeping the position of the object points fixed. In this […]

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