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Practical Mathematics For Ai And Deep Learning Tamoghna Ghosh

  • SKU: BELL-47493060
Practical Mathematics For Ai And Deep Learning Tamoghna Ghosh
$ 31.00 $ 45.00 (-31%)

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Practical Mathematics For Ai And Deep Learning Tamoghna Ghosh instant download after payment.

Publisher: BPB Publications
File Extension: EPUB
File size: 21.29 MB
Pages: 572
Author: Tamoghna Ghosh, Shravan Kumar Belagal Math
ISBN: 9789355511935, 9355511930
Language: English
Year: 2022

Product desciption

Practical Mathematics For Ai And Deep Learning Tamoghna Ghosh by Tamoghna Ghosh, Shravan Kumar Belagal Math 9789355511935, 9355511930 instant download after payment.

Mathematical Codebook to Navigate Through the Fast-changing AI Landscape KEY FEATURES ● Access to industry-recognized AI methodology and deep learning mathematics with simple-to-understand examples. ● Encompasses MDP Modeling, the Bellman Equation, Auto-regressive Models, BERT, and Transformers. ● Detailed, line-by-line diagrams of algorithms, and the mathematical computations they perform. 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 so that you can understand how any artificial intelligence system operates. 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. You will acquire knowledge that extends beyond mathematics while reading this book. Specifically, you will become familiar with numerous AI training methods, various NLP tasks, and the process of reducing the dimensionality of data. WHAT YOU WILL LEARN ● Learn to think like a professional data scientist by picking the best-performing AI algorithms. ● Expand your mathematical horizons to include the most cutting-edge AI methods. ● Learn about Transforme

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