There is a blog post by Peter Seibel: Let a 1,000 flowers bloom. Then rip 999 of them out by the roots. It has inspired other posts, for example (2) As a hobby Lisper I learned about Peter Seibel as the author of…
I can't understand this life style. To be the best at thinking deeply I need my mind to relax and focus in the goal, so to obtain a flux that point me in the direction to progress. Any anxiety or hurry is only going to…
Recently I read somewhere that people prefer "potential" to "factual value". For example some prefer a potential Oscar film rather than a film awarded an Oscar. So perhaps the new algorithm for fostering true telling…
Nice from one student: "I’m not worried about AI getting to where we are now. I’m much more worried about the possibility of us reverting to where AI is."
In 10.4 A/B testing is just a list with several points and there is not warning about having a deep understanding. For example, the point of selecting a sample is not easy, if you take a sample of something on 1 july of…
> I am working with people that don't understand even the basics (such as a survey with 49 responses means that the margin of error is over 10% I don't understand this, if the population if just 49 people then the…
When there is a small amount of information the variance of any estimation is very big and this explains what happens in that example. Overfitting implies a different behavior in training and in test and this is related…
There is a blog post by Peter Seibel: Let a 1,000 flowers bloom. Then rip 999 of them out by the roots. It has inspired other posts, for example (2) As a hobby Lisper I learned about Peter Seibel as the author of…
I can't understand this life style. To be the best at thinking deeply I need my mind to relax and focus in the goal, so to obtain a flux that point me in the direction to progress. Any anxiety or hurry is only going to…
Recently I read somewhere that people prefer "potential" to "factual value". For example some prefer a potential Oscar film rather than a film awarded an Oscar. So perhaps the new algorithm for fostering true telling…
Nice from one student: "I’m not worried about AI getting to where we are now. I’m much more worried about the possibility of us reverting to where AI is."
In 10.4 A/B testing is just a list with several points and there is not warning about having a deep understanding. For example, the point of selecting a sample is not easy, if you take a sample of something on 1 july of…
> I am working with people that don't understand even the basics (such as a survey with 49 responses means that the margin of error is over 10% I don't understand this, if the population if just 49 people then the…
When there is a small amount of information the variance of any estimation is very big and this explains what happens in that example. Overfitting implies a different behavior in training and in test and this is related…