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

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

[@codebasics]

Do you want to learn technology from me? Check codebasics.io/ for my affordable video courses

[@aravinthmegnath3569]

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 !

[@rahulranjan8682]

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 KZbin available for this topic.

[@harperjmusic]

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

[@codebasics]

Glad you liked it John

[@TheMarComplex]

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

[@kishlayamourya3141]

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.

[@longTomm]

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

[@mounikyerusu5058]

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

[@codebasics]

Glad it was helpful!

[@SeekingTruth0007]

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.

[@jyotigautam992]

This is the best explanation anyone could ask for! 😊

[@bhaskargg6018]

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

[@tanvirhasanmonir1627]

Amazing explanation as always. Thanks a lot for consistently providing quality content.

[@muhammadwaheedkhan5244]

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.

[@bigknp6211]

Thank you for such a great tutorial video. As you said on earlier on start video of your deep learning video series, concept are explained in very simple approach. It remind me the quote by A.E where he said "If you cannot explain in simple way , it means you didn't understood"

[@uchennanwosu5327]

Excellent exposition! I have seen some of your other videos in business statistics and they were equally accessible.

[@zurraiinrazali5369]

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

[@JapiSandhu]

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

[@phuonglethithanh8498]

Thank you for the explanation on precision and recall. Very easy to understand ❤

[@classicemmaeasy2292]

You are a real gem for this well detailed explanation

[@gauravpathak560]

Thanku sir It's help me to understand the behind the scene related to f1_score,precision and recall. Thanku so much again...

[@rndtest8691]

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

[@nikhilkshaji5165]

Thank for helping to understand these concepts.🥰❤

[@leilaamini405]

awesome. thanks a lot, you are very professional and teach very clear thank you

[@lllcdert826]

thank you very much the only video i managed to figure out the metrics

[@pankajyadav-en9cw]

The way you have explained these topics is fav bez I didn't get so clarity about these topic thank you explaining it means a lot 🙂

[@codebasics]

Glad you liked it pankaj

[@Spielerandom]

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

[@sanahnahk7312]

Thank you very much for making it simple.

[@kekkettoful]

Hello great video, apply the following classifiers: KNN, K-Me, Bayes, Binary Neural Networks and make a comparison between the results with the various techniques (through precision, recall, loss), also showing the confusion matrices, so as to report with which technique I get the best results. can you give me some advice please? Dataset is the 20 newsgroup text

[@ManikandanRaju]

Beautifully explained. Thank you so much sir

[@vivekverma9908]

This is the way to explain all these measures. Nice video

[@Susa270]

I am so Thankful to you. Crisp and Clear. 🙏 🙂

[@codebasics]

You are so welcome

[@devarapallivamsi7064]

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.

[@meysamjavadzadeh]

best confusion matrix explanation video . thanks👍

[@ilmu011]

One more question, in this example what would the "mean" average precision (mAP) be? And what's the difference between mAP and macro avg and micro avg

[@vanisameerayerramilli5049]

Brilliant Explanation!! Thanks a lot :)

[@adityawanjari5128]

Thank you for such wonderful explanation

[@Lena-of7wd]

You've explained this so clearly, thank you!!

[@codebasics]

Glad it was helpful!

[@sandiproy330]

Wonderful explanation. Very easy to understand. Nice clear step-by-step approach. Thanks for providing a such nice tutorial. thank you.

[@codebasics]

Glad it was helpful!

[@sjelallen]

Great explanation! Very helpful!

[@abdullahficici4298]

Crystal clear explanation. Thank you

[@codebasics]

Glad it was helpful!

[@gayathrisarangika2512]

Thankyou very much it is very clear explanation ❤❤

[@taufiqulhaque4987]

Each important evaluation metric in a nutshell... Thanks a lot

[@codebasics]

Glad it was helpful!

[@bluesky5166]

Good explanation about precision and recall.

[@chetanguduru]

Great expaination. Thanks for this!

[@MrAconfee]

Thank you! Great explanation.

[@abhishekranjan2617]

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

[@karlkfoury2213]

why genius lol

[@ahmedadnanaziz2005]

It is one of the best content ever seen 👏

[@meriemkh4382]

I swear this guy's the best

[@HotshotArafath]

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?

[@akbarboghani1]

Good explanation. How accuracy and precision are used in the real-world scenario? Can you share some references for the same

[@adityasharma2667]

Wondering who are these people who unlike this video!! Very Well explained!!! Thank you

[@codebasics]

Glad it was helpful!

[@leamon9024]

Always thanks for your effort and hard work.

[@codebasics]

My pleasure!

[@rishavbhattacharjee7182]

Brilliant Deep Learning Series sir😍

[@LifeAsWeSee678]

Thank you very much for explaining. I just couldn't get what does support means in the end of the video like at 11:07 . Thank you

[@azamshakori6926]

It was amazing, Thank u so much

[@HabiburRahamaniit]

Super Excellent explanation, Dhaval, Sir.

[@utn2609]

Thanks so much! Well explained!

[@codebasics]

Glad it was helpful!

[@uwebosch9460]

I loved it. Thank you

[@nnennaumelloh8834]

This is awesome! Thank you!

[@codebasics]

Glad it was helpful!

[@avani5381]

Wonderful explanation sir, kindly do some example in R language, that was so helpful for our work sir. Your way of explaination is extraordinary sir, support us with R language also . Once again Thank you for the picture example for our understanding.

[@ayoolafakoya9841]

You are an awesome teacher

[@artmispotter3571]

right to the point, thanks!

[@shibbirahmed7929]

Can you plz tell me how I can plot ROC curve for multilabel classification (5 labels of data) to compare various ML models accuracy?

[@developerboy8341]

Absolutely great presentation.

[@codebasics]

Glad it was helpful!

[@anuradhabalasubramanian9845]

Wonderful explanation Sir !

[@abdelatifhafid7934]

Thank you so much!

[@yepnah3514]

im a bit confused on how to set up the truth and prediction folder. the prediction folder contains the images we feed after the model has been trained right? but what about the truth folder?

[@PythonisLove]

Thanks this video helped a lot

[@mujamilkhan714]

Extremely waiting series🙌🏻

[@codebasics]

Glad it was helpful!

[@chinnumaria9145]

Thank you so much

[@dmarcolinok]

Great video!!!! Thank you!

[@codebasics]

I am glad this was helpful

[@MahibulHasanmahibul-hasan]

Very good explanation!

[@fahadreda3060]

Thanks for the video

[@greatfeedbackguy]

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

[@codebasics]

😀😀👍🏼

[@anmol_seth_xx]

Sir, Can you please tell me from these F1 score, what we can compute about our model, and what to do when we get these values?

[@kunalsinha962]

Best Explanation. Thankyou Sir

[@codebasics]

Glad it was helpful!

[@kalimuthudurairaj9191]

Good content... Nicely explained... Thank you...

[@codebasics]

I am happy this was helpful to you.

[@debatradas9268]

thank you so much

[@jassmalik4594]

Honestly it helped me a lot 🐱

[@aruneshprasad3064]

Could u tell me sir if any of the videos other than the GPU Benchmarking require cudannn and CUDA installation?

[@waedkhwies5550]

May I ask a question please? What are the required specifications for a deep learning training server? Thank you

[@shashwattiwari9666]

mast kaam krta h codebasics bhai tum

[@adamtki]

Excellent video!

[@mnal.abdulrahman]

Thank you soooooooo soooo much 😍😍🙏🙏🙏👌you helped me a lot

[@codebasics]

You're welcome 😊

[@faezeabdolinejad731]

its so good, thanks

[@chetangondaliya]

Thank you sir.

[@shadiyapp5552]

Thank you sir ♥️

[@rs9130]

Hello can you please make video on segmentation evaluation metrics like iou, precision, recall, ap and map for multi class. Thank you

[@borngenius4810]

thanks for these excellent videos. My question : do we used these Precsion, Recall , F1 parameters while using cross validaton method to chose a model?

[@jerichokayson2899]

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[@sonnybrecken3818]

@Jericho Kayson instablaster =)

[@jerichokayson2899]

@Sonny Brecken thanks so much for your reply. I got to the site on google and Im waiting for the hacking stuff atm. Looks like it's gonna take quite some time so I will get back to you later when my account password hopefully is recovered.

[@jerichokayson2899]

@Sonny Brecken It worked and I actually got access to my account again. I'm so happy:D Thanks so much you really help me out !

[@sonnybrecken3818]

@Jericho Kayson No problem xD

[@ramyaabin5548]

Sir you are Awesome. pls join as Amrita School of Computer Science Engineering we need lecturers like you.

[@mriduldongsare1555]

Very well explained

[@tarunbhatia8652]

Thanks!

[@sukanthenss914]

Nice sir.Thanks for sharing

[@ankitac4994]

Subscribed. Explained well!!

[@codebasics]

Glad it was helpful!

[@TechFromDan]

thanks so much man

[@currentactivities6527]

want to thank you, sir, this helps a lot, love from Pakistan.

[@codebasics]

😊👍

[@muskankuchhal2403]

Thank you so much for this amazing content. Sir, can you make the CNN tutorial? If yes, when can we expect it?

[@codebasics]

Yes, soon

[@kashifiqbal5151]

@@codebasics i am also waiting sir..

[@davidmercado2329]

thank you

[@abdelhafiddahhani2514]

Great explanation 😄

[@ayushgupta8538]

Thank you