Discover and read the best of Twitter Threads about #ML

Most recents (6)

Jonathan H Chen

@jonc101x

#Tweetorial on #Diagnostics and #Screening interpretation.
An otherwise healthy 40 year old woman comes to you after reading on the internet about a terrible disease that one in a thousand women get, and a highly accurate test that can save her life.

The test is over 99% accurate in people with the disease. For those without disease, the test is only wrong 5% of the time.

You order this test and it comes back positive. The woman anxiously asks you, do I have the disease? What is the chance this woman has the disease?

Assuming they weren't immediately fooled by the "test is only wrong 5 % of the time," most I've asked correctly recognize the stats provided are Sensitivity = 99% and Specificity = 95%, and that the objective is to determine the Positive Predictive Value.

Read 21 tweets

amcasari

@amcasari

Happening now: @jovialjoy is unpacking bias + #ML @lesbiantech #GHC18

@jovialjoy

Came late. But here goes..

Only requirement to join Algorithmic Justice League is to come up with a superhero name + a burning desire to help. @jovialjoy #GHC18

@jovialjoy

Companies are now moving towards algorithmic accountability l. Started work in 2016. Movement now. Joined IEEE to help with this work. TED talk over 1M views. @jovialjoy #GHC18 + @lesbiantech

Read 11 tweets

Ayo Philip

@Frawzey

Bayes’ Theorem Definitions:
The vertical bar | stands for "given that".
P = Probability.
A & B are events.
P(A) & P(B) are the probabilities of events A and B. Each event is separate from the other.
P(A|B) is the probability of A being true given that event B is true.
#SoDS18 #ML

Example:
Say we have 2 coolers at an owambe: Cooler A is filled with 10packs of small chops only. Cooler B has 5packs of small chops and 5packs of Asun. You are then asked to close your eyes and pick a pack out of one cooler, which pack would you pick? #MachineLearning #SoDS18

Because you know that we have more of small chops in both coolers, your brain is most likely going to tell you have picked a pack of small chops - even when your eyes are closed. This is not wrong.
#MachineLearning #SoDS18

Read 14 tweets

source{d}

@sourcedtech

@francesc

@francesc @vadimlearning First #MLonCode paper presented by @vadimlearning is "code2vec: Learning Distributed Representations of Code" by Uri Alon, Meital Zilberstein, @omerlevy_, and @yahave.

arxiv.org/abs/1803.09473

@francesc

@francesc @vadimlearning @omerlevy_ @yahave The second #MLonCode paper, also presented by @vadimlearning, is "A General Path-Based Representation for Predicting Program Properties" by ... wait for it ... Uri Alon, Meital Zilberstein, @omerlevy_, and @yahave 🎉

arxiv.org/abs/1803.09544