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Practical Mathematics For AI And Deep Learning

Shravan Kumar Belagal Math

Rs.879

Rs. 1,099

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Binding: Paper Back

Publisher: BPB Publications

Language: English

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Description

To construct a system that may be referred to as having ?Artificial Intelligence,? it is important to develop the capacity to design algorithms capable of performing data-based automated decision-making in conditions of uncertainty. Now, to accomplish this goal, one needs to have an in-depth understanding of the more sophisticated components of linear algebra, vector calculus, probability, and statistics. This book walks you through every mathematical algorithm, as well as its architecture, its operation, and its design. This book will teach you the common terminologies used in artificial intelligence such as models, data, parameters of models, and dependent and independent variables. The Bayesian linear regression, the Gaussian mixture model, the stochastic gradient descent, and the backpropagation algorithms are explored with implementation beginning from scratch. The vast majority of the sophisticated mathematics required for complicated AI computations such as autoregressive models, cycle GANs, and CNN optimization are explained and compared.

Additional Info

Author	Tamoghna Ghosh, Shravan Kumar Belagal Math
Publisher	BPB Publications
Language	English
Binding Type	Paper Back
Main Category	Science & Mathematics
Sub Category	Mathematics
ISBN13	9789355511935
SKU	BK 0179129