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HBR guide to AI basics for managers /
Get up to speed on AI-and start reaping the benefits now. From product design and financial modeling to performance management and hiring decisions-artificial intelligence and machine learning are becoming everyday tools for managers at businesses of all sizes. But the rewards of every AI system com...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | , |
| Formato: | Electrónico Audiom |
| Idioma: | Inglés |
| Publicado: |
[Place of publication not identified] :
Ascent Audio,
2023.
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| Edición: | [First edition]. |
| Colección: | Harvard business review guides.
|
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 246 | 3 | |a Harvard business review guide to AI basics for managers | |
| 246 | 3 | 0 | |a AI basics for managers |
| 246 | 3 | |a Artificial intelligence basics for managers | |
| 250 | |a [First edition]. | ||
| 264 | 1 | |a [Place of publication not identified] : |b Ascent Audio, |c 2023. | |
| 300 | |a 1 online resource (1 audio file (4 hr., 59 min.)) | ||
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| 520 | |a Get up to speed on AI-and start reaping the benefits now. From product design and financial modeling to performance management and hiring decisions-artificial intelligence and machine learning are becoming everyday tools for managers at businesses of all sizes. But the rewards of every AI system come with risks-and if you don't understand how to make sense of them, you're not going to make the right decisions. Whether you want to get up to speed quickly, could just use a refresher, or are working with an AI expert for the first time, HBR Guide to AI Basics for Managers will give you the information and skills you need. You'll learn how to: understand key terms and concepts; identify which of your projects and processes would benefit from an AI approach; deal with ethical issues before they come up; hire the best AI vendors; run small experiments; and work better with your AI experts and data scientists. Arm yourself with the advice you need to succeed on the job, with the most trusted brand in business. Packed with how-to essentials from leading experts, the HBR Guides provide smart answers to your most pressing work challenges. | ||
| 588 | 0 | |a Online resource; title from title details screen (O'Reilly, viewed January 10, 2023). | |
| 505 | 0 | |t Three Questions About AI That Every Employee Should Be Able to Answer : How does it work, what is it good at, and what should it never do? / |r by Emma Martinho-Truswell -- |t What Every Manager Should Know About Machine Learning : A non-technical primer / |r by Mike Yeomans -- |t The Three Types of AI : First, understand which technologies perform which types of tasks / |r by Thomas H. Davenport and Rajeev Ronanki -- |t AI Doesn't Have to Be Too Complicated or Expensive for Your Business : Focus on data quality, not quantity / |r by Andrew Ng -- |t How AI Fits into Your Data Science Team : Get over the cultural hurdles and avoid exaggerated claims / |r an interview with Hilary Mason -- |t Ramp Up Your Team's Predictive Analytics Skills : Three pitfalls your team needs to avoid / |r by Eric Siegel -- |t Assembling Your AI Operations Team : A top-notch model is no good if your people can't connect it to your existing systems / |r by Mark Esposito, Terence Tse, Takaai Mizuno, and Danny Goh -- |t How to Spot a Machine Learning Opportunity : What do you want to predict, and do you have the data? / |r by Kathryn Hume -- |t A Simple Tool for Making Decisions with AI : Use the AI Canvas / |r by Ajay Agrawal, Joshua Gans, and Avi Goldfarb -- |t How to Pick the Right Automation Project : Invest in the ones that will build your organization's capabilities / |r by Bhaskar Ghosh, Rajendra Prasad, and Gayathri Pallail -- |t Collaborative Intelligence : Humans and AI Are Joining Forces : They're enhancing each other's strengths / |r by H. James Wilson and Paul R. Daugherty -- |t How to Get Employees to Embrace AI : The sooner resisters get onboard, the sooner you will see results / |r by Brad Power -- |t A Better Way to Onboard AI : Understand it as a tool to assist people rather than replace them / |r by Boris Babic, Daniel L. Chen, Theodoros Evgeniou, and Anne-Laure Fayard -- |t Managing AI Decision-Making Tools : Humans still need to be involved : This framework will help you determine when and how / |t by Michael Ross | |
| 505 | 0 | |a And James Taylor -- |t Your Company's Algorithms Will Go Wrong : Have a Plan in Place : An AI designed to do X will eventually fail to do X / |r by Roman V. Yampolskiy -- |t A Practical Guide to Ethical AI : AI doesn't just scale solutions -- it also scales risk / |r by Reid Blackman -- |t AI Can Help Address Inequity -- If Companies Earn Users' Trust : A case from Airbnb shows how good algorithms can have negative effects / |r by Shunyuan Zhang, Kannan Srinivasan, Param Vir Singh, and Nitin Mehta -- |t Take Action to Mitigate Ethical Risks : It starts with three critical conversations / |r by Reid Blackman and Beena Ammanath -- How No-Code Platforms Can Bring AI to Small and Midsize Businesses : Three features to look for as you consider the right tool for your company / |r by Jonathon Reilly -- |t The Power of Natural Language Processing : NLP can help companies with brainstorming, summarizing, and researching. / |r by Ross Gruetzemacher -- |t Reinforcement Learning Is Ready for Business : Learning through trial and error can lead to more creative solutions / |r by Kathryn Hume and Matthew E. Taylor. | |
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 0 | |a Management |x Technological innovations. | |
| 650 | 0 | |a Business enterprises |x Information technology |x Management. | |
| 650 | 0 | |a Industrial management. | |
| 650 | 0 | |a Success in business. | |
| 650 | 6 | |a Intelligence artificielle. | |
| 650 | 6 | |a Gestion |x Innovations. | |
| 650 | 6 | |a Entreprises |x Technologie de l'information |x Gestion. | |
| 650 | 6 | |a Gestion d'entreprise. | |
| 650 | 6 | |a Succès dans les affaires. | |
| 650 | 7 | |a artificial intelligence. |2 aat | |
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| 650 | 7 | |a Industrial management |2 fast | |
| 650 | 7 | |a Management |x Technological innovations |2 fast | |
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| 700 | 1 | |a Miller, Rich, |e narrator. | |
| 700 | 1 | |a Kay, Cindy, |e narrator. | |
| 710 | 2 | |a Harvard Business Review Press, |e issuing body. | |
| 830 | 0 | |a Harvard business review guides. | |
| 856 | 4 | 0 | |u https://learning.oreilly.com/library/view/~/9781663722591/?ar |z Texto completo (Requiere registro previo con correo institucional) |
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