The culture and growth of scientific research in various domains are interesting to observe. For many decades traditional scientific research has been accessible or done in academia or research institutes. Each decade or century witnessed various sciences rising to the limelight. Once it was physical sciences, then it was biological science, the age of computers,
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The field of information theory defines entropy as a measure of average information a random variable takes. As we know the random variable is one whose possible outcome states are not deterministic. We cannot predict its behavior exactly in an analytical form. In such cases, we can only look at the patterns of its outcome
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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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This article is a review of active learning which is a subfield of machine learning Introduction The field of Machine Learning (ML) broadly deals with giving computers the ability to do tasks like humans. We are seeing a human-level performance in specialized tasks such as speech recognition, image recognition, etc. Many sub-fields of ML are
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The topic I wish to talk in this post is about Mathematical maturity. It is connected to the abstract nature of mathematics and humans’ endeavor to cope with it. Let me start by asking you a question. Have you ever seen a circle in real-life?. You might say yes because we all draw many in
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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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This post is a summary of various machine learning career advices by experts in this domain. Introduction The field of machine learning and artificial intelligence is very promising. The scientific progress and interest in the field are increasing every day. The applicability of the ideas into multiple fields makes it attractive to people from a
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Introduction Divide and conquer seem the most widely used strategy to attack hard problems. The use of this idea and similar approaches are ample in every discipline. In this post, let’s look at how this concept is a cornerstone in analyzing signals and systems. Consider the case of audio signals. We can think of them
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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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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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