Category Archives: Data Science

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An attempt to understand deep neural nets using the Information Bottleneck theory

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At the very core of Deep Learning lies a silent demon called the optimization problem; While deep learning has pretty much started reshaping businesses, business processes and our lives in various ways, many of us still don’t have a clear understanding about the algorithm(s) governing it. This article is an attempt to understand how Deep […]

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Mysteries of the ROC curve

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Most Data Scientists would have come across the ROC (receiver operating characteristic) curve. It is often used to evaluate the performance of a binary classifier by measuring AUC (area under the curve) and to find an optimal probability threshold to get to the sweet spot in the sensitivity-specificity tradeoff. However, both theoretically and practically there […]

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Segmentation of Images using Deep Learning

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In computer vision, image segmentation is the process of dividing an image into parts and extracting the regions of interest. More precisely, image segmentation is the process of assigning a label to every pixel in an image such that pixels having similar characteristics have the same label. Historically, most problems in computer vision involved using […]

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Medical Video Analytics and Deep Learning

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A wise person once said “A picture speaks a thousand words” citing the amount of information that is self-contained in a picture. Along the same lines, it wouldn’t be grossly wrong to say that “A video illustrates a thousand pictures”. Needless to say, the amount of information that can be extracted from a video is […]

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