Автор: Teik Toe Teoh, Yu Jin Goh
Издательство: Springer
Серия: Machine Learning: Foundations, Methodologies, and Applications
Год: 2023
Страниц: 385
Язык: английский
Формат: pdf (true)
Размер: 10.8 MB
Artificial Intelligence (AI) is rapidly gaining significance in the business world. With more and more organizations adopt AI technologies, there is a growing demand for business leaders, managers, and practitioners who can harness AI’s potential to improve operations, increase efficiency, and drive innovation.
This book aims to help management professionals exploit the predictive powers of AI and demonstrate to AI practitioners how to apply their expertise in fundamental business operations. It showcases how AI technology innovations can enhance various aspects of business management, such as business strategy, finance, and marketing. Readers interested in AI for business management will find several topics of particular interest, including how AI can improve decision-making in business strategy, streamline operational processes, and enhance customer satisfaction.
As AI becomes an increasingly important tool in the business world, this book offers valuable insights into how it can be applied to various industries and business settings. Through this book, readers will gain a better understanding of how AI can be applied to improve business management practices and practical guidance on how to implement AI projects in a business context. This book also provides practical guides on how to implement AI projects in a business context using Python programming. By reading this book, readers will be better equipped to make informed decisions about how to leverage AI for business success.
Part I of the book aims to help readers build up their knowledge of common Artificial Intelligence algorithms, through the explanations of various algorithms and simple Python examples provided. On the other hand, Part II highlights different problems faced by business management professionals across core business functions and illustrates how Artificial Intelligence could be utilized to alleviate them.
In the Chapter 8, we will explore the speech to text capabilities with Python, and then we will assemble a seq2seq long short-term memory (LSTM) model using Keras Functional API to create an example chatbot that would answer questions asked to it. You can try integrating both programs together. However, do note that the code we have provided does not integrate both components. Chatbots have become applications themselves. You can choose the field or stream and gather data regarding various questions. We can build a chatbot for an e-commerce website or a school website where parents could get information about the school. Messaging platforms such as Allo have implemented chatbot services to engage users. The famous Google Assistant, Siri, Cortana, and Alexa were built using similar models.
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