Weekend Reading List

Weekend List for Sep 23, 2018

Bullshit jobs – one of my favorite topics. And a reminder that we all must never find ourselves in a soul destroying job



“Getting positive or negative reactions to something you do or say is a greater influence on your thinking than logic and reasoning, the new research suggests – so if you’re in a group of like-minded people, that’s going to reinforce your thinking.” So very true … and underscores the importance of learning (which has feedback as a key part) over knowing


The gap between a Data Scientist and the Software Engineer continues to close. Is ML Engineer the new thing?


A good example of combining NLP and ML at scale


Useful design concepts for a world of multiple data stores – from transaction systems to analytical environments. Replication, propagation et al. become critical



Weekend List for Sep 9,2018

Machine Learning does need human guidance – from labeling training datasets to the judgment element for Reinforcement Learning systems. There is obvious interest in creating autonomous learning systems. Watch out for more …


The idea of treating data as an asset has finally taken root. The time has to come to relevant data into a ‘first-class’ organization object


Scale doesn’t happen overnight – but while you are waiting for scale, what do you do? From the founder of Airbnb


How businesses that scale will succeed


Interesting article


Weekend List for Aug 31, 2018

‘Demo or Die’ – sums it all up


Food for thought – esp. for those of us who are drinking the koolaid in the Valley


Black box or not? Relevant debate


In the world of ‘fake news’ …


Will this help the pesky problem of black swan events in Forecasting …


Weekend List for Aug 25/26, 2018

Nice article on Questions – we always knew that questions are important. Some interesting research to formalize this

AI is the new hype – and the odds of delivering successful outcomes are still quite low. Good read on how to think about AI projects

We live in a culture that disproportionately celebrates heroes. Even more so in domains where individual brilliance and effort creates value – Physics being one. Popular culture has reinforced this stereotype over and over again. This is a good piece on looking beyond the individuals at their mentors – and the attention their contribution deserves.

Good thought starter on applications of reinforcement learning – outside of the gaming world, this has not found many applications. That should not be so: agent-environment interactions with feedback situations exist aplenty: Customer Care Interactions; Supply Chain Inventory positions; Web personalization are examples

Pure, unadulterated fun. However, what is amazing is the rigor with which he breaks a big problem into components, with nothing more than thinking from first principles. Something to learn

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