Title
Recommendation Engines (The Mit Press Essential Knowledge Series),Used
Delivery time: 8-12 business days (International)
How Companies Like Amazon And Netflix Know What You Might Also Like: The History, Technology, Business, And Social Impact Of Online Recommendation Engines.Increasingly, Our Technologies Are Giving Us Better, Faster, Smarter, And More Personal Advice Than Our Own Families And Best Friends. Amazon Already Knows What Kind Of Books And Household Goods You Like And Is More Than Eager To Recommend More; Youtube And Tiktok Always Have Another Video Lined Up To Show You; Netflix Has Crunched The Numbers Of Your Viewing Habits To Suggest Whole Genres That You Would Enjoy. In This Volume In The Mit Press'S Essential Knowledge Series, Innovation Expert Michael Schrage Explains The Origins, Technologies, Business Applications, And Increasing Societal Impact Of Recommendation Engines, The Systems That Allow Companies Worldwide To Know What Products, Services, And Experiences You Might Also Like.Schrage Offers A History Of Recommendation That Reaches Back To Antiquity'S Oracles And Astrologers; Recounts The Academic Origins And Commercial Evolution Of Recommendation Engines; Explains How These Systems Work, Discussing Key Mathematical Insights, Including The Impact Of Machine Learning And Deep Learning Algorithms; And Highlights User Experience Design Challenges. He Offers Brief But Incisive Case Studies Of The Digital Music Service Spotify; Bytedance, The Owner Of Tiktok; And The Online Personal Stylist Stitch Fix. Finally, Schrage Considers The Future Of Technological Recommenders: Will They Leave Us Disappointed And Dependentor Will They Help Us Discover The World And Ourselves In Novel And Serendipitous Ways?
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⚠️ WARNING (California Proposition 65):
This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.
For more information, please visit www.P65Warnings.ca.gov.
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Shipping
We ship your order within 2–3 business days for USA deliveries and 5–8 business days for international shipments. Once your package has been dispatched from our warehouse, you'll receive an email confirmation with a tracking number, allowing you to track the status of your delivery.
Returns
To facilitate a smooth return process, a Return Authorization (RA) Number is required for all returns. Returns without a valid RA number will be declined and may incur additional fees. You can request an RA number within 15 days of the original delivery date. For more details, please refer to our Return & Refund Policy page.
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Warranty
We provide a 2-year limited warranty, from the date of purchase for all our products.
If you believe you have received a defective product, or are experiencing any problems with your product, please contact us.
This warranty strictly does not cover damages that arose from negligence, misuse, wear and tear, or not in accordance with product instructions (dropping the product, etc.).
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Frequently Asked Questions
- Q: What is the main topic of 'Recommendation Engines' by Michael Schrage? A: The book explores the history, technology, and societal impact of recommendation engines, explaining how companies like Amazon and Netflix suggest products and content based on user preferences.
- Q: Who is the author of 'Recommendation Engines'? A: The author is Michael Schrage, an innovation expert known for his insights into technology and its applications in business.
- Q: How many pages are in 'Recommendation Engines'? A: The book contains 296 pages.
- Q: What type of binding does 'Recommendation Engines' have? A: The book is available in paperback binding.
- Q: When was 'Recommendation Engines' published? A: The book was published on September 1, 2020.
- Q: What category does 'Recommendation Engines' fall under? A: The book is categorized under 'Storage & Retrieval'.
- Q: Does 'Recommendation Engines' include case studies? A: Yes, the book includes brief case studies of companies like Spotify, ByteDance (owner of TikTok), and Stitch Fix.
- Q: What can readers learn about the future of recommendation engines from this book? A: Readers will learn about the potential future developments of recommendation engines and their impact on user experience and discovery.
- Q: Is 'Recommendation Engines' suitable for someone without a technical background? A: Yes, the book is written to be accessible to a general audience, providing insights into both technical and practical aspects of recommendation systems.
- Q: Are there any particular technologies discussed in 'Recommendation Engines'? A: The book discusses key technologies such as machine learning and deep learning algorithms that power recommendation systems.