Conceptual

Active Learning with Uncertainty Sampling from Scratch

This article is a tutorial on the algorithm called active Learning with uncertainty Sampling. Introduction Availability of mass quantities of digital data and feasible computing power brought to the creation of learning algorithms. These learning algorithms have been benchmarked to perform specialized tasks such as classification, object detection, image segmentation, etc. The key assumption here …

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Magnetic Refrigeration Technology

Why does it need to look for an alternate cooling technology? Cooling appliances based on thermodynamic cycle till 1995 used to produce many toxic components Chloroflurocarbon CFC), Hydrochloroflurocarbon (HCFC), potent greenhouse gases (GHG) and other ozone depleting substances (ODC). After gradual prohibition of such gases, the cooling appliances till date producing HFCs which have no …

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RL Tutorial from Center for Brains Minds and Machines

The Center for Brains, Minds and Machines (CBMM) is a premier institute and NSF Science and Technology Center dedicated to the study of intelligence. The website and Youtube channel of the institute contains a good number of tutorials and educational materials that help anyone interested in topics related to neuroscience, machine intelligence, etc. One of …

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Sugar Cube Falling

A World of small things: Introduction to Nanotechnology

Nanotechnology deals with the science of building small, but why do we talk about such small things? Well, they ultimately constitute the world we live in and we can explore fascinating things with them, literally, it can shape the world around us. Properties of materials change due to quantum effects when they are made small, …

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Bivariate Gaussian Distribution

Hacking the Bivariate Gaussian Distribution

In one of our earlier posts, we have seen how we can visually relate the parts of the one-dimensional Gaussian distribution equation. In this post, we will follow the same strategy to understand the terms that comes up with a Multivariable Gaussian distribution. We will focus on the Bivariate Gaussian distribution as distributions of higher-order …

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minmax scaling

Visualizing MinMax Scaling

This article explains the minmax scaling operation using visual examples. Normalization of vectors, an array of values, signals is often used as a preprocessing step before many algorithms. For example, in machine learning, some types of algorithms are prone to different inherent scales of features. In such situations normalization is done to give the same …

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