The national Academic Networks that are part of RedCLARA are non-for-profit organizations and do not represent any type of trademark. Linear Algebra and Mathematical Foundation: This course covers machine learning key elements, vector space, matrices, linear independence and basis and linear maps. Mathematica is a modern technical computing system that covers most areas of the discipline, such as neural networks, machine learning, image processing. If your country is not on the list above, please write to. de Mathematica Aplicada e Computacional (SBMAC), which was created in 1978. Mathematica 11 includes many new machine learning capabilities. With the help of mathematics, we can input these dimensions into a computer, and linear algebra is about processing new data sets. As a discipline, machine learning covers a lot of ground. Where humans see an image, a computer will see a 2D- or 3D-matrix. Costa Rica - RedCONARE, please write to: Weinan E is the director of the Center for Machine Learning Research at. Math is needed for machine learning because computers see the world differently from humans. Argentina - InnovaRed, please write to:. This contribution is part of the collaborative actions that the National Research and Education Networks (NREN) of Latin America are coordinating, together with RedCLARA, to support our member institutions in the fight against Coronavirus (COVID-19).įor more information about these or other free of charge services to face the situation caused by the pandemic, please contact the national network of your country:
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