How Machine Learning is Innovating Today’s World A Concise Technical Guide



Free Download How Machine Learning is Innovating Today’s World
by Arindam Dey

English | 2024 | ISBN: 1394214111 | 477 pages | True PDF | 56.22 MB


Provides a comprehensive understanding of the latest advancements and practical applications of machine learning techniques.
Machine learning (ML), a branch of artificial intelligence, has gained tremendous momentum in recent years, revolutionizing the way we analyze data, make predictions, and solve complex problems. As researchers and practitioners in the field, the editors of this book recognize the importance of disseminating knowledge and fostering collaboration to further advance this dynamic discipline.How Machine Learning is Innovating Today’s Worldis a timely book and presents a diverse collection of 25 chapters that delve into the remarkable ways that ML is transforming various fields and industries.
It provides a comprehensive understanding of the practical applications of ML techniques. The wide range of topics include:
An analysis of various tokenization techniques and the sequence-to-sequence model in natural language processingexplores the evaluation of English language readability using ML modelsa detailed study of text analysis for information retrieval through natural language processingthe application of reinforcement learning approaches to supply chain managementthe performance analysis of converting algorithms to source code using natural language processing in Javapresents an alternate approach to solving differential equations utilizing artificial neural networks with optimization techniquesa comparative study of different techniques of text-to-SQL query conversionthe classification of livestock diseases using ML algorithmsML in image enhancement techniquesthe efficient leader selection for inter-cluster flying ad-hoc networksa comprehensive survey of applications powered by GPT-3 and DALL-Erecommender systems’ domain of applicationreviews mood detection, emoji generation, and classification using tokenization and CNNvariations of the exam scheduling problem using graph coloringthe intersection of software engineering and machine learning applicationsexplores ML strategies for indeterminate information systems in complex bipolar neutrosophic environmentsML applications in healthcare, in battery management systems, and the rise of AI-generated news videoshow to enhance resource management in precision farming through AI-based irrigation optimization.
Audience
The book will be extremely useful to professionals, post-graduate research scholars, policymakers, corporate managers, and anyone with technical interests looking to understand how machine learning and artificial intelligence can benefit their work.

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