helping robots conquer the earth and trying not to increase entropy using Python, Data Engineering and Machine Learning
Check out my blog - http://luminousmen.com
Thank you for your comment!
Yes, you're right - humans are bad estimators. But firstly, the project/time should be estimated anyway and secondly, by collecting several opinions your estimate more likely will be in realistic range.
How so?
If you ask people how the weather will be tomorrow, the estimation doesn't get more accurate depending on the number of people you ask. But why do we believe that to be true for project management?
Perhaps ML will improve estimations rather than humans guessing.
helping robots conquer the earth and trying not to increase entropy using Python, Data Engineering and Machine Learning
Check out my blog - http://luminousmen.com
It's simple. It called the wisdom of the crowd - individuals may be totally wrong but the whole crowd will be quite accurate. There are several methods of ML based on this paradigm as you mention ML here =) - bagging for example
For further actions, you may consider blocking this person and/or reporting abuse
We're a place where coders share, stay up-to-date and grow their careers.
Humans are bad at estimations. There are essentially two problems here:
a) Most humans have too few datapoints in mind to make a realistic prognosis
b) Most humans are biased, mostly seeing things too optimistic
There was an insightful episode on freakonomics radio: Here’s Why All Your Projects Are Always Late — and What to Do About It
In order to improve the situation, you have to decrease the "human factor".
Thank you for your comment!
Yes, you're right - humans are bad estimators. But firstly, the project/time should be estimated anyway and secondly, by collecting several opinions your estimate more likely will be in realistic range.
How so?
If you ask people how the weather will be tomorrow, the estimation doesn't get more accurate depending on the number of people you ask. But why do we believe that to be true for project management?
Perhaps ML will improve estimations rather than humans guessing.
It's simple. It called the wisdom of the crowd - individuals may be totally wrong but the whole crowd will be quite accurate. There are several methods of ML based on this paradigm as you mention ML here =) - bagging for example