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When you search something on Google your search result are displayed by a theorem called Bayes theorem.
Netflix uses it for its Recommendations
Hedge funds , self driving cars, Spam filters all uses Bayes theorem
When you search something on Google your search result are displayed by a theorem called Bayes theorem.
Netflix uses it for its Recommendations
Hedge funds , self driving cars, Spam filters all uses Bayes theorem
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What is Bayes theorem?
A simple mathematical formula which helps us understand and deal with uncertainty.
Humans mind think in binaries
Good- bad , black - white.
We are confused when it comes to interpret grey areas.
What is Bayes theorem?
A simple mathematical formula which helps us understand and deal with uncertainty.
Humans mind think in binaries
Good- bad , black - white.
We are confused when it comes to interpret grey areas.
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Bayes theorem help us rationalise those grey areas.
When we come across a new evidence abt something, it helps us update our beliefs and create a new belief.
In a nutshell the theorem help us quantify or put a number on our own skepticism and help us make rational choices.
Bayes theorem help us rationalise those grey areas.
When we come across a new evidence abt something, it helps us update our beliefs and create a new belief.
In a nutshell the theorem help us quantify or put a number on our own skepticism and help us make rational choices.
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The theorem is based on basic algebra.
To use the formula all you need
to do is remember the three ingredients, find them, and plug them in.
You will then have an updated probability based on new
information which is technically called the Posterior
Probability.
The theorem is based on basic algebra.
To use the formula all you need
to do is remember the three ingredients, find them, and plug them in.
You will then have an updated probability based on new
information which is technically called the Posterior
Probability.
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Using this formula Alan Turing broke the enigma code.
In 1998 Microsoft applied for a spam filter patent that used a Bayesian filter.
Googleâs driverless cars use a form of Bayesian
modeling to help the vehicle know its location
http://stanford.edu/~cpiech/cs221/apps/driverlessCar.html">https://stanford.edu/~cpiech/c...
Using this formula Alan Turing broke the enigma code.
In 1998 Microsoft applied for a spam filter patent that used a Bayesian filter.
Googleâs driverless cars use a form of Bayesian
modeling to help the vehicle know its location
http://stanford.edu/~cpiech/cs221/apps/driverlessCar.html">https://stanford.edu/~cpiech/c...
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Apart from its use in technology thinking in Bayesian terms can help us in decision making.
The key to using Bayes
theorem in everyday decision making is to make rough calculations quickly in
your mind that will help you discover the odds of an event,not the probability.
Apart from its use in technology thinking in Bayesian terms can help us in decision making.
The key to using Bayes
theorem in everyday decision making is to make rough calculations quickly in
your mind that will help you discover the odds of an event,not the probability.
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DATING
So, hereâs one way of how Bayes& #39; Theorem can be applied to dating.
You are dressed in your finest and on a date one Friday night.
You like this girl but you are utterly confused. Does she like you? Is she into you?
Sheâs been laughing and flirting with you.
DATING
So, hereâs one way of how Bayes& #39; Theorem can be applied to dating.
You are dressed in your finest and on a date one Friday night.
You like this girl but you are utterly confused. Does she like you? Is she into you?
Sheâs been laughing and flirting with you.
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What we are going to do is find four numbers and quickly compute them.
Remember, all numbers are rough beliefs that you are quickly putting together in
your mind.
What we are going to do is find four numbers and quickly compute them.
Remember, all numbers are rough beliefs that you are quickly putting together in
your mind.
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Step 1:
Let& #39;s assign some probability numbers.
Number 1: Guess the probability that she likes you regardless of anything else.
Based on your past dating success, youâd say this is 20%. You think at least 2/10
girls will like you.
Number 1 = 2
Step 1:
Let& #39;s assign some probability numbers.
Number 1: Guess the probability that she likes you regardless of anything else.
Based on your past dating success, youâd say this is 20%. You think at least 2/10
girls will like you.
Number 1 = 2
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Number 2: Guess the probability that she doesnât like you regardless of anything
else. Based on our answer above, if your past history tells you that your dates
like you 2/10 times, that means your date will not like you 8/10 times, or 80%.
Number 2 = 8
Number 2: Guess the probability that she doesnât like you regardless of anything
else. Based on our answer above, if your past history tells you that your dates
like you 2/10 times, that means your date will not like you 8/10 times, or 80%.
Number 2 = 8
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Number 3: Guess the probability of your date laughing and flirting if she likes
you. Considering that she is flirting, you guess that there is a 90% chance of this.
Number 3 = 9
Number 3: Guess the probability of your date laughing and flirting if she likes
you. Considering that she is flirting, you guess that there is a 90% chance of this.
Number 3 = 9
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Number 4: Guess the probability of your date laughing and flirting if she doesnât like you. You think this is low, so you guess 10%.
Number 4 = 1
Number 4: Guess the probability of your date laughing and flirting if she doesnât like you. You think this is low, so you guess 10%.
Number 4 = 1
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Step 2:
Line your numbers up as ratios.
Step 2:
Line your numbers up as ratios.
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Step 3: Multiply down and simplify.
Conclusion:
Step 3: Multiply down and simplify.
Conclusion:
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Conclusion:
Based on a quick calculation, the odds that she likes you are 9 to 4, or slightly
greater than 2 to 1. What does this
mean? This means it is roughly twice as likely that she likes you as opposed to not liking you.
Conclusion:
Based on a quick calculation, the odds that she likes you are 9 to 4, or slightly
greater than 2 to 1. What does this
mean? This means it is roughly twice as likely that she likes you as opposed to not liking you.
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This theorem has changed the world by being at the epicenter of technology.
But it has its downsides to.
It is a great thinking framework but its use in social media algorithms is polarizing the world.
Let& #39;s see how this theorem is shaping our world views.
This theorem has changed the world by being at the epicenter of technology.
But it has its downsides to.
It is a great thinking framework but its use in social media algorithms is polarizing the world.
Let& #39;s see how this theorem is shaping our world views.
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An Initial Belief + New Evidence = A New, Updated Belief.
This is the core of Bayes theorem.
We have a initial belief and we logged on to twitter.
We saw a new evidence ,a tweet similar to our views liked it and retweeted it.
An Initial Belief + New Evidence = A New, Updated Belief.
This is the core of Bayes theorem.
We have a initial belief and we logged on to twitter.
We saw a new evidence ,a tweet similar to our views liked it and retweeted it.
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Now according to Bayes theorem this new evidence is updated as a new belief for the algorithm and in turn it starts showing all the similar post.
Now at the same time your beliefs are also getting shaped and updated with new evidence.
Now according to Bayes theorem this new evidence is updated as a new belief for the algorithm and in turn it starts showing all the similar post.
Now at the same time your beliefs are also getting shaped and updated with new evidence.
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Everyday by consuming the tailored feed curated by the Bayes theorem.
Algorithms which updates it& #39;s feed with new evidences through the input we are giving and in return our beliefs are updated by new evidence our feeds are giving us.
Everyday by consuming the tailored feed curated by the Bayes theorem.
Algorithms which updates it& #39;s feed with new evidences through the input we are giving and in return our beliefs are updated by new evidence our feeds are giving us.
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A scary loop of Initial belief
https://abs.twimg.com/emoji/v2/... draggable="false" alt="đ" title="Nach rechts und links zeigende Pfeile in offenem Kreis im Uhrzeigersinn" aria-label="Emoji: Nach rechts und links zeigende Pfeile in offenem Kreis im Uhrzeigersinn"> New evidence https://abs.twimg.com/emoji/v2/... draggable="false" alt="đ" title="Nach rechts und links zeigende Pfeile in offenem Kreis im Uhrzeigersinn" aria-label="Emoji: Nach rechts und links zeigende Pfeile in offenem Kreis im Uhrzeigersinn"> Updated belief.
This is how social media is shaping our world view.
A scary loop of Initial belief
This is how social media is shaping our world view.
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This thread is dedicated to awesome thinkers on twitter.
( @SahilBloom)( @paraschopra ) ( @EricRWeinstein)( @dickiebush) ( @ShaanVP) ( @mariodgabriele) ( @alexgarcia_atx) ( @warikoo)
( @paraschopra)
If you like this thread you can follow me for more @slaphacks
This thread is dedicated to awesome thinkers on twitter.
( @SahilBloom)( @paraschopra ) ( @EricRWeinstein)( @dickiebush) ( @ShaanVP) ( @mariodgabriele) ( @alexgarcia_atx) ( @warikoo)
( @paraschopra)
If you like this thread you can follow me for more @slaphacks
