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Jobs-to-Be-Done in Your UX Toolbox
A brilliant overview of JTBD as an overarching framework, with good references.
jtbd  innovation  design  productmanagement  management 
yesterday by gerwitz
Hypothesis Kit 3 – Craig Sullivan – Medium
Thanks to Colin Mcfarland, Lukas Vermeer, Rik Higham, Doug Hall, Michael Aagard and many others who helped shape this. 9/11 : V3 updated after Feedback from RH — to change within x business cycles to…
hypotheses  productmanagement 
2 days ago by rchrd_h
Product Management Today
Industry insights your peers are reading. The very best industry content from the Product Management Today community.
4 days ago by cera
The Business Implications of Machine Learning –
Nearly all computation takes place off-device. The bulk of computation is the creation of the models, which requires access to the massive dataset created by all users. Hence, model construction cannot take place on the device or per customer.
fortalk  ai  productmanagement 
8 days ago by pskomoroch
Balancing Machine Learning And Human Intuition In The Travel Industry
Have you ever gone through an entire hotel or flight booking process, only to be told at the end the item was unavailable? Like many industries, travel companies suffer from inconsistency in data. Due to a slew of legacy systems, changes in hotel and airline databases might not fully propagate in time to booking providers to reflect real-time supply. To combat this problem, Kayak’s algorithms analyze a wide variety of historical sources to generate a more accurate forecast of availability.
productmanagement  ai  ml  fortalk 
8 days ago by pskomoroch
Data: A key requirement for your Machine Learning (ML) product
In most cases, more data is better than less.
If little or no data are available, transfer learning may help. In short, transfer learning allows you to take data and/or ML models from one task (e.g. classify dog breeds) and apply them to other tasks (e.g. classify cars). More on that in a future blog post.
In cases where acquiring labeled data costs money (and/or time), define a goal of where you want to get to (in terms of model quality/performance) and a threshold of how much money/time you are willing/able to spend.
At some point, more data will not help.
If you are looking for more information on this topic, try searching “power analysis for testing distribution similarity”.
productmanagement  ml  ai  fortalk 
8 days ago by pskomoroch
No Machine Learning in your product? Start here – The Lever – Medium
ML improves an existing feature (e.g. increased accuracy of a recommendation system)
ML as an enabler for entirely new features (e.g. photo search by content rather than keyword)
ML as an enabler for entirely new products (e.g. driverless cars)
productmanagement  ai  fortalk 
8 days ago by pskomoroch
The full stack product manager – UX Collective
I paired up with the one-and-only Michael Lopp to facilitate the session and it was truly one of the most interesting a-ha conversations that I’ve had the opportunity to take part in for a while…
9 days ago by twleung
How to Hire a Product Manager - The classic essay on the role of product management - Ken Norton
Why did you decide to move from engineering to product management?
What is the biggest advantage of having a technical background?
What is the biggest disadvantage?
What was the biggest lesson you learned when you moved from engineering to product management?
What do you wish you’d known when you were an engineer?
How do you earn the respect of the engineering team?
product  productmanagement  interview 
10 days ago by pskomoroch

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