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Showing posts with label Free. Show all posts
Showing posts with label Free. Show all posts

Friday, April 21, 2023

Free MIT Press Book on Deep Learning

 An MIT Press book   https://www.deeplearningbook.org/ 

Ian Goodfellow and Yoshua Bengio and Aaron Courville

The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular. The online version of the book is now complete and will remain available online for free.

The deep learning textbook can now be ordered on Amazon.

For up to date announcements, join our mailing list.

Citing the book

To cite this book, please use this bibtex entry:

@book{Goodfellow-et-al-2016,
    title={Deep Learning},
    author={Ian Goodfellow and Yoshua Bengio and Aaron Courville},
    publisher={MIT Press},
    note={\url{http://www.deeplearningbook.org}},
    year={2016}
}

To write your own document using our LaTeX style, math notation, or to copy our notation page, download our template files.

Errata in published editions

NVIDIA Text to Video

 https://www.youtube.com/watch?v=30epFM6Vb0s

147,333 views  Apr 19, 2023  #chatgpt #AI #Robotics

NVIDIA's NEW AI 'Text To Video Takes the Industry By STORM! (NOW UNVEILED!)

https://research.nvidia.com/labs/toronto-ai/VideoLDM/

Welcome to our channel where we bring you the latest breakthroughs in AI. From deep learning to robotics, we cover it all. Our videos offer valuable insights and perspectives that will expand your knowledge and understanding of this rapidly evolving field. Be sure to subscribe and stay updated on our latest videos.

Was there anything we missed?

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#AI

Thursday, January 07, 2021

Limitations of a Fremium Approach to Marketing

Thoughtful examination of the approach of free ... and the idea of freemium. 

Don’t Count on Free Trials to Win You Customers  in HBR, by Sadat Reza, Dixon Ho, Rich Ling, Hongyan Shi, and Gemma Calvert

January 07, 2021

Summary.   The authors’ research provides evidence that for “experience” goods– those where value is only discovered after consumption, for example a holiday destination, a movie, or new software — free trial campaigns should be deliberately targeting existing customers of medium to high usage. For this...   more

Everybody loves a freebie. That’s probably why so many start-ups and even well-known brands often use free trials to draw customers’ attention and introduce them to new products. Yet free trials often fail to convert customers to paying ones. Even when they do convert, customers obtained using free trials can be significantly less valuable than other customers. The problem, our recent research suggests, is that too many free trial campaigns aim to bring new customers to a brand’s products rather than enticing existing customers to spend more. If this is true, our research can help marketers find the sweet spot for free trials.

When freebies work

In our study, we collaborated with a major mobile phone operator in a developing market, where the average usage of mobile data services was much lower compared to the developed market. The marketing team of the company sent out 60MB free mobile data — about an hour of low-resolution video streaming through the web — offer to 60,000 subscribers of their mobile phone services. The offer receiving subscribers were randomly chosen from the pool of subscribers who used smart-phones and used SMS services but had different levels of exposure to using mobile data, including non-users and heavy-users.

We anticipated that nonusers of mobile data would be more likely to redeem the offer and increase usage after the campaign. To our surprise, it turned out that the low usage customers were largely unresponsive to the trial offer and the campaign failed to stimulate higher usage among these customers. Customers familiar with using a lot of data did take advantage of the trial offer, but we found that their data usage didn’t change during the trial period. Our third group of customers — those who use a medium to high amount of data regularly — were most likely to redeem the offer and we also found that their data usage increased after the campaign. Lastly, we also found that peer effect matters. When the company gave some customers the option to forward the free trial to peers (who were also existing customers) they were more likely to redeem the offer.

Our research provides evidence that for “experience” goods — for example a holiday destination, a movie, or new software, where value is only discovered after consumption — free trial campaigns should be deliberately targeting existing customers of medium to high usage. Our study reveals that for this type of goods and services, relative to non-users, customers with some exposure to the product are more responsive to free-trial campaigns.   ... '