Article

Reimagining Businesses with AI

<p>Discover what AI can do for your business with this approachable and comprehensive resource</p><p>Reimagining Businesses with AI acquaints readers with both the business challenges and opportunities presented by the rapid growth and progress of artificial intelligence. The accomplished authors and digital executives of the book provide you with a multi-industry approach to understanding the intersection of AI and business.</p><p>The book walks you through the process of recognizing and capitalizing on AI’s potential for your own business. The authors describe:</p>How to build a technological foundation that allows for the rapid implementation of artificial intelligenceHow to manage the disruptive nature of powerful technology while simultaneously harnessing its capabilitiesThe ethical implications and security and privacy concerns raised by the spread of AI<p>Perfect for business executives and managers who seek a jargon-free and approachable manual on how to implement artificial intelligence in everyday operations, Reimagining Businesses with AI also belongs on the bookshelves of anyone curious about the interaction between artificial intelligence and business.</p> <br><br> Publisher ‏ : ‎ Wiley; 1st edition (October 20, 2020) <br> Language ‏ : ‎ English <br> Hardcover ‏ : ‎ 304 pages <br> ISBN-10 ‏ : ‎ 1119709156 <br> ISBN-13 ‏ : ‎ 978-1119709152 <br> Item Weight ‏ : ‎ 1.35 pounds <br> Dimensions ‏ : ‎ 7.1 x 1.2 x 9.9 inches <br>

Discount Price: [price_with_discount]


(as of [price_update_date] - Details)

[ad_1]

Description


Reimagining Businesses with AI
-

Discover what AI can do for your business with this approachable and comprehensive resource

Reimagining Businesses with AI acquaints readers with both the business challenges and opportunities presented by the rapid growth and progress of artificial intelligence. The accomplished authors and digital executives of the book provide you with a multi-industry approach to understanding the intersection of AI and business.

The book walks you through the process of recognizing and capitalizing on AI’s potential for your own business. The authors describe:

How to build a technological foundation that allows for the rapid implementation of artificial intelligenceHow to manage the disruptive nature of powerful technology while simultaneously harnessing its capabilitiesThe ethical implications and security and privacy concerns raised by the spread of AI

Perfect for business executives and managers who seek a jargon-free and approachable manual on how to implement artificial intelligence in everyday operations, Reimagining Businesses with AI also belongs on the bookshelves of anyone curious about the interaction between artificial intelligence and business.



Publisher ‏ : ‎ Wiley; 1st edition (October 20, 2020)
Language ‏ : ‎ English
Hardcover ‏ : ‎ 304 pages
ISBN-10 ‏ : ‎ 1119709156
ISBN-13 ‏ : ‎ 978-1119709152
Item Weight ‏ : ‎ 1.35 pounds
Dimensions ‏ : ‎ 7.1 x 1.2 x 9.9 inches

-[ad_2]

Rating


Rating Star: 5

Related Reads

R
ai-book
Real Fake: Playing with Reality in the Age of AI, Deepfakes and the Metaverse
ai-book

Real Fake: Playing with Reality in the Age of AI, Deepfakes and the Metaverse

Get on a rollercoaster of disinformation and media manipulation. From lying hieroglyphs to computer-generated influencers and the future of deepfakes. People have always felt the need to play with reality, but never before has it been so easy and believable as now. How do we keep a grip on the information society now that artificial intelligence is getting involved in the manipulation game? Unlike most books about fading realities, Real Fake looks beyond the doom scenarios. Using inspiring restoration stories and a new set of Reality Ethics, the authors of Real Fake outline a hopeful future for the playful human.<br><br><br>“Real Fake educates, terrifies, and stimulates simultaneously. Nascent synthetic media technology has the potential to create mayhem or happiness for society -- the authors brilliantly paint a picture of how this battle will play out over the next ten years. And most interestingly, they predict the "democratization of creativity" -- how the new digital tools will unleash a dynamic and vital era of marketing, commerce, and art.” George F. Colony, CEO, Forrester<br><br>"As someone who has studied authenticity (real vs. fake) and the rise of digital technology (real vs. virtual), no one has intertwined these topics in as interesting, insightful, and indispensable a narrative as the authors of Real Fake. Digital technology is giving us something akin to superpowers. Will we use them to obliterate the distinctions between authenticity and inauthenticity, reality and virtuality, human and machine? Or will we find a path into a future that preserves what makes us human while ennobling our technology in service to our innate needs? Real Fake says yes."<br>-- B. Joseph Pine II, co-author, The Experience Economy: Competing for Customer Time, Attention, and Money<br><br>“An extremely authentic book!” Daisy Williams, virtual human <br><br> Publisher ‏ : ‎ Ludibrium publishers (September 21, 2021) <br> Language ‏ : ‎ English <br> Paperback ‏ : ‎ 296 pages <br> ISBN-10 ‏ : ‎ 9493170683 <br> ISBN-13 ‏ : ‎ 978-9493170681 <br> Item Weight ‏ : ‎ 13.7 ounces <br> Dimensions ‏ : ‎ 5.5 x 0.74 x 8.5 inches <br>

Read more →
T
ai-book
The Handbook of Artificial Intelligence, 3 Volume Set
ai-book

The Handbook of Artificial Intelligence, 3 Volume Set

Describes the basic concepts and latest techniques for the programming of computers to duplicate the human thinking process <br><br> Publisher ‏ : ‎ William Kaufmann & HeurisTech Press (December 1, 1982) <br> Language ‏ : ‎ English <br> ISBN-10 ‏ : ‎ 0865760047 <br> ISBN-13 ‏ : ‎ 978-0865760042 <br> Item Weight ‏ : ‎ 2.35 pounds <br>

Read more →
L
ai-book
Linear Algebra and Optimization for Machine Learning: A Textbook
ai-book

Linear Algebra and Optimization for Machine Learning: A Textbook

<p>This textbook introduces linear algebra and optimization in the context of machine learning. Examples and exercises are provided throughout the book. A solution manual for the exercises at the end of each chapter is available to teaching instructors. This textbook targets graduate level students and professors in computer science, mathematics and data science. Advanced undergraduate students can also use this textbook. The chapters for this textbook are organized as follows:</p><p>1. Linear algebra and its applications: The chapters focus on the basics of linear algebra together with their common applications to singular value decomposition, matrix factorization, similarity matrices (kernel methods), and graph analysis. Numerous machine learning applications have been used as examples, such as spectral clustering, kernel-based classification, and outlier detection. The tight integration of linear algebra methods with examples from machine learning differentiates this book from generic volumes on linear algebra. The focus is clearly on the most relevant aspects of linear algebra for machine learning and to teach readers how to apply these concepts.<br></p><p>2. Optimization and its applications: Much of machine learning is posed as an optimization problem in which we try to maximize the accuracy of regression and classification models. The “parent problem” of optimization-centric machine learning is least-squares regression. Interestingly, this problem arises in both linear algebra and optimization, and is one of the key connecting problems of the two fields.  Least-squares regression is also the starting point for support vector machines, logistic regression, and recommender systems. Furthermore, the methods for dimensionality reduction and matrix factorization also require the development of optimization methods. A general view of optimization in computational graphs is discussed together with its applications to back propagation in neural networks. <br></p><p>A frequent challenge faced by beginners in machine learning is the extensive background required in linear algebra and optimization. One problem is that the existing linear algebra and optimization courses are not specific to machine learning; therefore, one would typically have to complete more course material than is necessary to pick up machine learning. Furthermore, certain types of ideas and tricks from optimization and linear algebra recur more frequently in machine learning than other application-centric settings. Therefore, there is significant value in developing a view of linear algebra and optimization that is better suited to the specific perspective of machine learning.</p><p></p> <br><br> Publisher ‏ : ‎ Springer; 1st ed. 2020 edition (May 13, 2020) <br> Language ‏ : ‎ English <br> Hardcover ‏ : ‎ 516 pages <br> ISBN-10 ‏ : ‎ 3030403432 <br> ISBN-13 ‏ : ‎ 978-3030403430 <br> Item Weight ‏ : ‎ 2.61 pounds <br> Dimensions ‏ : ‎ 7 x 1.13 x 10 inches <br>

Read more →
U
ai-book
Ultimate Step by Step Guide to Machine Learning Using Python: Predictive modelling concepts explained in simple terms for beginners
ai-book

Ultimate Step by Step Guide to Machine Learning Using Python: Predictive modelling concepts explained in simple terms for beginners

*Start your Data Science career using Python today!*<br>Are you ready to start your new exciting career? Ready to crush your machine learning career goals?<br><br>Are you overwhelmed with complexity of the books on this subject?<br><br>Then let this breezy and fun little book on Python and machine learning models make you a data scientist in 7 days!<br><br>First part of this book introduces Python basics including:<br>•Data Structures like Pandas <br>•Foundational libraries like Numpy, Seaborn and Scikit-Learn<br><br>Second part of this book shows you how to build predictive machine learning models step by step using techniques such as:<br>•Regression analysis<br>•Decision tree analysis<br>•Training and testing data models<br>•Tensor Flow, Keras and PyTorch<br>•Additional data science concepts like Classification Analysis, Clustering, Association Learning and Dimension Reduction<br><br>The final part of the book provides a structured framework on how to solve real world problems using data science and how to structure your data science project. <br><br>After reading this book you will be able to:<br>•Code in Python with confidence<br>•Build new machine learning models from scratch<br>•Know how to clean and prepare your data for analytics<br>•Speak confidently about statistical analysis techniques<br><br>Data Science was ranked the fast-growing field by LinkedIn and Data Scientist is one of the most highly sought after and lucrative careers in the world!<br><br>If you are on the fence about making the leap to a new and lucrative career, this is the book for you!<br><br>What sets this book apart from other books on the topic of Python and Machine learning: <br>•Step by step code examples and explanation<br>•Complex concepts explained visually<br>•Real world applicability of the machine learning models introduced<br>•Bonus free code samples that you can try yourself without any prior experience in Python!<br><br><br>What do I need to get started?<br><br>You will have a step by step action plan in place once you finish this book and finally feel that you, can master data science and machine learning and start lucrative and rewarding career! <br><br>Ready to dive in to the exciting world of Python and Machine Learning?<br><br>Then scroll up to the top and hit that BUY BUTTON!<br><br> <br><br> ASIN ‏ : ‎ B084WGCMG1 <br> Publication date ‏ : ‎ February 16, 2020 <br> Language ‏ : ‎ English <br> File size ‏ : ‎ 2363 KB <br> Text-to-Speech ‏ : ‎ Enabled <br> Screen Reader ‏ : ‎ Supported <br> Enhanced typesetting ‏ : ‎ Enabled <br> X-Ray ‏ : ‎ Not Enabled <br> Word Wise ‏ : ‎ Not Enabled <br> Sticky notes ‏ : ‎ On Kindle Scribe <br> Print length ‏ : ‎ 70 pages <br>

Read more →