Introduction to R Software

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Overview Any scientific task without the knowledge of software is difficult to imagine and complete in the current scenario. R is a free software that is capable of handling mathematical and statistical manipulations. It has its own programming language as well as built in functions to perform any specialized task. We intend to learn the basics of R software in this course.

Computational Continuum Mechanics

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Introduction - origins of nonlinearity, Mathematical Preliminaries -1: Tensors and tensor algebra, Mathematical Preliminaries -2: Linearization and directional derivative, Tensor analysis etc

Artificial Intelligence Search Methods for problem Solving

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Overview For an autonomous agent to behave in an intelligent manner it must be able to solve problems. This means it should be able to arrive at decisions that transform a given situation into a desired or goal situation. The agent should be able to imagine the consequence of its decisions to be able to identify the ones that work. In this first course on AI we study a wide variety of search methods that agents can employ for problem solving.

Tools in Scientific Computing

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Overview Rapid advancements in computer hardware and high quality software libraries have enabled one to undertake works requiring high precision scientific computing with relative ease. The course involves exploration of various tools available for scientific computing with an emphasis on hands-on implementation. The course will deal briefly with the theory and the associated implementation for practical problems that an engineer may encounter. Undergraduates, postgraduates, and PhD students may find this course immensely useful for their project or research work. The course will make use of Python, GNU Octave, and PETSC (C based) as the medium of coding.

Pattern Recognition I

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Lecture Details Pattern Recognition by Prof. C.A. Murthy & Prof. Sukhendu Das,Department of Computer Science and Engineering,IIT Madras.For more details on NPTEL visit httpnptel.ac.in

Pattern Recognition

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Lecture Details Pattern Recognition by Prof. P.S. Sastry, Department of Electronics & Communication Engineering, IISc Bangalore. For more details on NPTEL visit httpnptel.ac.in

Convolutional Neural Networks for Visual Recognition

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Overview Computer Vision has become ubiquitous in our society, with applications in search, image understanding, apps, mapping, medicine, drones, and self-driving cars. Core to many of these applications are visual recognition tasks such as image classification, localization and detection.