LSTM Recurrent Neural Network (RNN) | Explained in Detail

[@dmg-s]

I am so happy now. Thanks!

[@abhinavbuddala4620]

😂

[@ivana_ftn]

You are better than my professor, thank you

[@MachineLearningWithJay]

@@ivana_ftn Haha… glad to hear! Means a lot. Thank you!

[@hafolahbi]

I can't pass without commenting and liking this video. It is invaluable, far more than reading it in journals

[@MachineLearningWithJay]

Wow.. thank so much for such an amazing comment! Means a lot to me. Glad I could help. I wish you all the very best for your exams!

[@srishti6637]

best explanation with no faltu pnchyti and made the topic crystal clear

[@MachineLearningWithJay]

Thanks! 😁

[@bigfuckingdeal9474]

1000000000% agree

[@eng.mohamedemam6489]

from a man from Egypt send big thanks to you ❤❤

[@MachineLearningWithJay]

Your welcome

[@Ayoub.Naderei]

I think u deserve much more than 27k subscribers man. I totally got it after watching this playlist

[@MachineLearningWithJay]

Hehe! Thank you so much! I appreciate it, and I agree. Hopefully with more videos and your support, the channel might grow.

[@ikraamhanif7966]

Kash mene phly prh liya hota aj paper hai aur apki videos dekh kr itna achay sy smjh arha hai kiya hi bolun apko...Thank u so much for providing us knowledge like this

[@MachineLearningWithJay]

Hi, I am elated from your words. Glad it was helpful.

[@jayhu6075]

I am very glad to find your channel. You make this topic for a beginner as me so understandable. Hopefully a following to write this in a python code. Many thanks.

[@rajkamal1705]

Very easy to understand. You are better than many prof. Thanks bro.

[@MachineLearningWithJay]

@@rajkamal1705 Thank you! It means a lot!

[@nikhils2155]

Thank you for these awesome classes brother

[@MachineLearningWithJay]

You’re welcome!

[@christianfaust5141]

Thank you from Germany, I appreciate your work

[@MachineLearningWithJay]

Great to be greeted! You’re welcome

[@s8x.]

brother u made learning machine learning so easy. When i got money i will be sure to show my thanks

[@MachineLearningWithJay]

@@s8x. haha… you appreciating this is enough for me me! Goad I could help!

[@tridibeshmisra9426]

Best explanation...... It helped me for endsem exam...thank u sir.....keep creating ... let's get riding🙂🙂

[@MachineLearningWithJay]

@@tridibeshmisra9426 Glad I could help! Hope your endsem went well

[@MurodilDosmatov]

Thousand of thanks for your effort to make this video tutorial

[@MachineLearningWithJay]

Happy that it was valuable. Thanks for the compliment!

[@pavangoyal6840]

Excellent. Thank for this video and explaining complex concept like LSTM in very short and crisp video

[@MachineLearningWithJay]

@@pavangoyal6840 Glad I could help!

[@Thing1Thing11]

Thank you so much! I was so lost and you really helped me get to grips with what is going on

[@MachineLearningWithJay]

@@Thing1Thing11 Glad I could help!

[@rezamohammadi1140]

Very helpful because of mathematical explanation and summery in the last

[@MachineLearningWithJay]

@@rezamohammadi1140 Thank you! Glad to help!

[@arvinflores5316]

That was a good binge man. Hopefully attention/transformers will be covered too!

[@MachineLearningWithJay]

Thanks for the suggestion... I will try to cover those too

[@deepurachakonda28]

u made my day..thnx lot

[@MachineLearningWithJay]

My pleasure 😊

[@dinushachathuranga7657]

Thanks for the clear explanation ❤❤

[@MachineLearningWithJay]

You're welcome! I am glad you found this helpful! 😄

[@khushiyadav-st4oh]

Best Explanation Ever

[@MachineLearningWithJay]

@@khushiyadav-st4oh Thanks you so much!

[@Bunches_of_Entertaiment]

Superb explanation brother.. thank you so much 😍.. I got very clear understand on LSTM and as well as RNN

[@MachineLearningWithJay]

@@Bunches_of_Entertaiment Happy to help!

[@vinayakmane7569]

remarkable explanation , keep bringing good content. just one little suggestion , try to write keypoints on board while explaining so that we can copy and it will help us while revising

[@MachineLearningWithJay]

@@vinayakmane7569 Write may be I will try to keep the summary at the end and write key points there? Would it help? Anyways I will keep this in mind for my future videos

[@muhammadumarwaseem]

Thank you for the detailed to the point explanation.

[@KulkarniPrashant]

Clear and concise explanation, thank you!

[@saatvikkool]

You're doing a great job bro ✌️❤️

[@MachineLearningWithJay]

Thank you so much 😊

[@kavoshgar9733]

You describe everything very well✌️

[@sandeepkomalpothu44]

thanks man …. very helpful … cheers !!!

[@MachineLearningWithJay]

Cheers!!

[@sandeepkomalpothu44]

@@MachineLearningWithJay could you please make videos on GRUs ,se2seq,Attention models, Transformers?

[@MachineLearningWithJay]

@@sandeepkomalpothu44 I am goong to upload those videos, but it will take some time. Right now, i am busy with my exams, so will upload when i get time. 😇

[@harshitraj8409]

Great Explanation

[@MachineLearningWithJay]

Thank you

[@INCREDIBLE9463]

Very good explanation

[@QuratRaja-q2v]

Worthy explanation!

[@PRAJAKTAPATKAR-t7z]

Amazing- great work

[@evildead3734]

Great resources 🙌

[@MachineLearningWithJay]

Thanks

[@hamedhasani5774]

awesome work

[@juditmaymo9714]

love this video!!

[@this_is_the_baat]

thanks my dear bro

[@Animelover-oo7cz]

you are the best thank youu

[@shaveta01]

Good vdo Pl use white marker 😊instead of red

[@7aanusha885]

thank you for this video

[@user_userovich]

Thank you very much!

[@achreflegend4335]

5:00 the green formula ; shouldn't it be a sum of multiplication through 0~t instead of just a sum

[@vishnusit1]

At 8:45 you are wrong about matrix multiplication

[@pavangoyal6840]

For time series data (there are around 60 input variables) and there are two outputs variables. Which deep learning model would be best LSTM ? Here accuracy matters. For learning time does not matter. For 2 output variables how to design LSTM model ?

[@tanvirtanvir6435]

3:22 problem with RNN

[@iftikharullah3616]

I watched many videos for this topic but couldn't understand it. You made every point clear in a beautiful way 🫡

[@rohitpol1109]

What is Bc, Bf, Bi, Bo added everywhere ?? Is that bias ?

[@forsakennawfal546]

Biases or as we can say the Constants added in every function, indicating the margin of error.

[@KhadijaTulKubra-o2o]

Hi! i want to learn text detection from images using RNN. Please if you can help ???

[@VenomOmpi]

thanks a lot!

[@mainakmukherjee3444]

Hello bhaiya, thanks for the informative contents. But can you please explain me why you are saying ft (forget gate) is a matrix. From the formula, it just an output of a sigmoid function, which I think a scalar value for each time step. Please explain this part. 🙏🙏

[@KishorA-s8f]

Thank you

[@slingshot7602]

Tnx a lot

[@ABCD-wd1sk]

Thanks

[@MachineLearningWithJay]

@@ABCD-wd1sk you’re welcome

[@beshosamir8978]

Hi , i hope one day you explain transformers because ur explainations is great ,but i really need your help about something because i really got tired of searching about the answer i got stucked on something and seems like no one helps so i hope you help me , now i studied about LSTM and Bi-LSTM and i understood them well , but i read some blogs said that bi directional LSTM good for sentiment analysis and time series so i really got confused about it , How it could be useful !!!! it will be useful if my current prediction depends on what happens in the future ,so how it could be usefull in sentiment analysis if i already will predict my final output in the last word so there is no future because i stand in the last , i know it could be usefull in some applications like name entity recognation because the type of the output is (many) so maybe my current output depends on what is happend in the future i really hope to help me because i didn't find any reason after 2 hours of searching in google

[@MachineLearningWithJay]

Hi, bidirectional LSTM looks at all the words appearing in an input sentence, from both directions, front to back and back to front. So, you can always assume that bidirectional LSTM can be useful for any application involving sentences as input. I don’t have any more reason for this, for now.

[@beshosamir8978]

@@MachineLearningWithJay So , is my question make sense ? or there's something i can not understood about the intuation for now ?

[@aitoquantum]

the summation formula is wrong! one product sum should be there along with plain summation, that will unfold the longer terms...

[@slingshot7602]

GRU???

[@charanm1773]

Arigatto

[@tahsinulkarim]

❤❤❤

[@martinant44]

te quiero mucho

[@MrKhanRizwan]

Too complex must be targeted for mathematicians

[@MachineLearningWithJay]

Hi, yeah… the details LSTM is a bit complicated. It doesn’t make much sense at first, and you need mathematical background to understand this. If you are not concerned with the implementation details, then you can directly use LSTM through frameworks like PyTorch, Keras

[@shantanusingh2198]

Proably the worst video on lstm i have seen

[@MachineLearningWithJay]

Amm.... sure... All videos are different kind... sad to see this tutorial wasn't help to you :(