Precision, Recall, F1 score, True Positive|Deep Learning Tutorial 19 (Tensorflow2.0, Keras & Python)

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In this video we will go over following concepts,
What is true positive, false positive, true negative, false negative
What is precision and recall
What is F1 score
We will also write simple code to compare dog vs non dog labels and print all above measures on them

#Whatistruepositive #falsepositive #truenegative #falsenegative #precisionandrecall #F1score #deeplearning

#️⃣ Social Media #️⃣

DISCLAIMER: All opinions expressed in this video are of my own and not that of my employers'.

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This is the best explanation on performance metrics that I've found so far.

harperjmusic

I have 4 years of experience in data domain and whenever I go for interview I come to this video to revise this concept.
This is actually the best video on YouTube available for this topic.

rahulranjan

Honestly this is the best explanation I have ever seen. I have been studying ML for the past 3 months and have gone through many tutorials. This video straight away cleared my confusions about the confusion matrix. Thank You so much Dev !

aravinthmegnath

This was some seriously brilliant explanation. Takes patience and passsion. Thank you.

mischievousmaster

Finally. An explanation of precision and recall that makes sense! Great stuff

longTomm

Simple and straightforward explanation, Thank you very much, sir. My only suggestion is to put two or more topics in a slide and discuss them together, such as when relating the confusion matrix concept to precision and recall.

SeekingTruth

Thanks a lot!!!
Only video that clearly explained precison and recall of BOTH the classes. I really gets confused after observing the results of sklearn classification report as mostly I was explained that positives are important den go for precision and if neg imp go for recall ...also tried to understand by formula but no use. Finally its clear. Thanks again.

kishlayamourya

Thank you so much! 🙌🏻Very well explained. From Germany.

Spielerandom

Your explanation is so clear and the complex confusion matrix concept is Clearly understood, Thank you

bhaskargg

You are a real gem for this well detailed explanation

classicemmaeasy

Good explanation about precision and recall.

bluesky

Nice explained. A suggestion -> also discuss the *WHENs* of each concept you explain.

Like, when we use Precisio, Recall, and F1-Score.

By the way, great work.

muhammadwaheedkhan

Excellent explanation, would have been complete if you have also explained why we need F1 score along when we have precision and recall in place.
Thank you for the concise and to the point illustration.

devarapallivamsi

you are a true genious sir....

Your way of teaching and explanation is awesome sir..
I love this video😎😎😘😘☺☺👌👌❤❤🥰🥰😍😍🙏🙏🙏🙏🙏🙏

abhishekranjan

Awesome explanation These are ever confusing topics .... Which are made so simple in this tutorial...

rndtest

Thank you so much! You are the best teacher ever!

TheMarComplex

Yup, finally found the best explanation on classification report.. + easy to understanddd

zurraiinrazali

This is the most intuitive video on this topic. Thanks.

JapiSandhu

Sir can we apply this metrics in to the potato leaf disease detection project? And should we apply them before or after building the cnn model?

HotshotArafath

Very well explained with precision, hence really easy to recall!

greatfeedbackguy

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