Long Short-Term Memory (LSTM), Clearly Explained
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- Опубликовано: 19 май 2024
- Basic recurrent neural networks are great, because they can handle different amounts of sequential data, but even relatively small sequences of data can make them difficult to train. This is where Long Short-Term Memory (LSTM) saves the day. Long Short-Term Memory is a type of recurrent neural network that can handle much larger sequences of data without those pesky exploding/vanishing gradient problems that plague basic recurrent neural networks.
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0:00 Awesome song, introduction and main ideas
4:19 The sigmoid and tanh activation functions
5:58 LSTM Stage 1: The percent to remember
9:25 LSTM Stage 2: Update the long-term memory
12:42 LSTM Stage 3:Update the short-term memory
14:33 LSTM in action with real data
#StatQuest #LSTM #Dubbedwithaloud
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NOTE: Since LSTM is a type of neural network, we find the best Weights and Biases using backpropagation, just like for any other neural network. For more details on how backpropagation works, see: ruclips.net/video/IN2XmBhILt4/видео.html ruclips.net/video/iyn2zdALii8/видео.html and ruclips.net/video/GKZoOHXGcLo/видео.html The only difference with LSTMs is that you have to unroll them for all of your data first and then calculate the derivatives. In the example in this video, that means unrolling the LSTM 4 times (as seen at 17:49) and calculate the derivatives for each variable, starting at the output, for each copy and then add them together.
ALSO NOTE: A lot of people ask why the predictions the LSTM makes for days other than day 5 are bad. The reason is that in order to illustrate how, exactly, an LSTM works, I had to use a simple example, and this simple example only works if it is trained to predict day 5 and only day 5.
you deserve a a shamless promotion for this lecture dude.
@@enggm.alimirzashortclipswh6010 Thank you! :)
"At first I was scared of how complicated the LSTM was, but now I understand."
"TRIPLE BAM!!!"
Thanks Dr. Starmer for teaching in a way I could follow. I am placing an order for your book today.
Hooray!!! Thank you very much! :)
As someone who has watched a ton of videos on these topics, I can say that you probably do the best job of explaining the underlying functionality in a simple to follow way. So many other educators put up the standard flowchart for a model and then talk about it. Having the visual examples of data going in and changing throughout really helps hammer the concept home.
Thank you very much!
great great great great great great great great great great great great great great video!
@@suzhenkang Thank you very much! :)
yes definitely
@@statquest also cool sound effects
the first stage of LSTM unit determines what percentage of long term memory is remembered ... you are absolutely amazing!
Bam! :)
2 years into Data science, many paid an unpaid courses, never understood the underlying functionality of LSTM but today, Thank you Mr. Josh Starmer for being in my life.
BAM! :)
Some rare teachers have instant cred. The moment they start talking you are convinced they really understand the subject and are qualified to teach it. As an experienced teacher of extremely challenging tech myself, I confess that I've never seen more complete and polished preparation. You are changing people's lives at just the moment when this is so critical. Best of everything to you.
Thank you very much! I really appreciate it.
Thanks StatQuest for everything!
TRIPLE BAM!!! Thank you so much for supporting StatQuest!!!
The ease with which you explain these topics has inspired me to pursue a masters in data science. Thank you for helping me unveil my passion.
One can learn any thing for passion. should invest money and time learning in only employable courses.
BAM! :)
I have been working in ML industry of 5 years now. But I never had this clear understanding. Not only have you explained this clearly but also sparked a curiosity to understand everything with this much clarity. Thanks Josh!!
Thank you! :)
I have been waiting for your LSTM video for so long! No other videos can explain ML concepts as good as you do, you sir deserve a thousand BAMs!!
Thank you very much! BAM! :)
Man the timing! I just saw your RNN video yesterday and was waiting for your LSTM video. Your timing is just impeccable
Perfect!
Mad respect for putting in the hours to prepare the material for the course. These topics are some of complicated ones and yet your illustration + explanation + awesome songs make it easy and enjoyable.
Thank you very much! :)
For a beginner, your videos make me feel easy to follow and understand. I love the way that you use the visual example with different colors so that it easier to follow. And the curiosity to learn more is the thing that makes your videos really impressive to me. Thank you, Josh!
Awesome, thank you!
Josh, your videos and book have been an incredible discovery for me. The visual explanation is much easier to understand. Thank you!
Thank you very much! :)
I read and watched various articles and videos about LSTM, but none of them explained as well and simply as you. I learned a lot from your video and I am indebted to you. Thank you for taking the time to make this video. I hope you are always healthy and happy. BAM :)
Thank you!
I have never fully understood the working of LSTM and tried many blogs and videos on it until I watched your video. This is by far the best explanation on LSTM I have seen on internet. Thank you so much for putting so much of hard work in creating these types of videos.
Glad it helped!
Such a wonderful explanation. Have been learning about LSTMs in my course but finally understand how it works now. Looking forward to the next step of the Quest!
Thanks!
Your videos should begin with "universities hate this guy, learn how you increase your knowledge with Josh" 😂
BAM! :)
The university I'm in is hiring new professors, I wish Josh Starmer is my statistics professor, lol
Universities actually love they can use these videos as material.
Litterally got recomended the channel by my professor, so i would say that necessarilly
@@Ragnarok540 Yes, they can afford giving poor classes because students will study on their own. Essentially making degrees useless.
I clicked like before watching the video but after 5 seconds of scrolling through the visualizations.
You have some of the best visualizations on this topic on RUclips.
Glad I found your channel.
An exceptional explanation! I finally understand LSTMs after 6 months of trying to get my head around them! Thank you so much.
Glad it was helpful!
Damn, these are very well explained. The somewhat silly humor isn't quite for me, but with these high quality explanations I couldn't care less about that. Great job!
Thanks! :)
I was learning about LSTM for the last two months; still struggled to understand what exactly happening inside until I watched this video. Huge thanks for the content creator. Still, I am struggling about the weights and bias values. Please make your next video on that, if possible.
Once again, Thank you so much.
The weights and biases are optimized with backpropagation, which I explain in these videos: ruclips.net/video/IN2XmBhILt4/видео.html ruclips.net/video/iyn2zdALii8/видео.html and ruclips.net/video/GKZoOHXGcLo/видео.html
Gosh, Josh. You make learning such a breeze. Thank you very much for every single BAM!
BAM! :)
Requested a video on NLP some time ago and here StatQuest with a better explanation than I expected! (Other RUclipsrs and Courses taught me 'How LSTM works?' but your explanation taught 'Why LSTM works?' The clarification between sigmoid and tanh solved many of my questions)
Hooray! :)
BEST TEACHER EVER! seriously how do you make such complicated matters so simple and easy to understand? You're amazing and even tho I didn't plan on learning Machine learning, I'm soooo gonna watch every last video on this channel! thank you for this!
Thank you very much! :)
This is an awesome video to explain LSTM. I have a little knowledge about LSTM (I felt that is required to understand this video) - but you made it really clear and eloquent. Your voice is perfect and clear. Hats off !! Thank you so much
Glad it was helpful!
Definitely the best visual explanation of LSTM I have ever seen!! Can't wait for your video for Transformers.
Glad you liked it!
@@statquest Do you have any timeline in mind for a video on Transformers?
This is the best tutorial so far. Thank you for your clearly explanation! I watched every episode of your NN series. I am a CS student and building a voice cloning app for my honour project. Your tutorials are truly helpful!!!
Thanks! I'm really glad my videos are helpful! :)
Use simple words to help me understand some complex concepts! Really appreciated that! Looking forward to learning Transformers from you soon!
Thanks! :)
Your videos always puts a smile on my face, while learning.
Hooray! :)
i think this is the most clear explanation of LSTM i've ever seen. i've watched many other videos that teaches LSTM, but none of them made me feel so clear about this thing!
Thank you!
This is the best video to clearly explain the concept of LSTM I have ever seen!
BAM!
I can't go to the next video without saying a big thanks to you here !! loved this explanation !! 👏
Thank you! 😃!
This tutorial was too good!!
Now I clearly know how LSTMs work, and how they are used to solve the Vanishing/Exploding Gradient Descent problem.
Thank you StatQuest!!
BAM! :)
Your videos are very accessible, I love them. I'll definitely recommend them when I'm asked for introductions to Machine Learning content.
Awesome! Thank you! :)
Just WOW! Can't wait to see the third part of this series (Transformers). Thank you, Josh.
Thanks! :)
How does this channel not have 100 million subscribers already? What a beautiful content. Love the way things are presented.
Thank you! :)
Dr. Starmer, you're a rockstar! Your videos are a life-saver. I use your videos as supplementary training as I go through other ML/DL/AI courses. The visualizations are amazing and your explanations are equally amazing. 😎👊
Glad to help!
Thank you so much for continuing to upload videos on this machine learning topic!! Your videos has saved my grade a year ago and now it has helped my team members understand the concept very easily!
Thanks!
This weekend I'll try going to church to thank god for your existence Josh, seriously
bam! :)
I have watched almost all of your videos from the beginning ... I found that your teaching skills and visualization skills become better and better in every single video. This is the best quality of a data scientist, which I do not find in many data scientists.
Wow, thanks!
As usual, the best intuitive explanation i have seen for LSTM till now! I have banged my head on this topic in thousands of literature and videos who try to explain the same block diagrams over and over.. I got frustrated beyond a certain point. Thankfully Josh made this.. Atleast from a concept wise I am clear now..What Josh does to the community is commendable..
Thank you very much! :)
Thank you so much! I became a payed member. I wish you great success in your passion for teaching.
Awesome, thank you!
Excellent introduction to LSTMs. Thank you Josh
Thank you!
Can't thank you enough! the dedication you put in this video is amazing. You are my guru (or shall I call it Yoda).
Wow, thank you!
Thank you professor, you are the best!
Thanks!
Finally, I understood LSTM. Clean and simple explanation. Probably the best one about LSTM.
Thank you! :)
Thank you so much for all of your tutorials, Josh! Really clearly explained and very helpful!
Glad you like them!
I'm taking an NLP class, we learned about LSTMs a couple weeks ago. I have already forgotten much. This was a very clear and well illustrated example of how they work. Hopefully the percentage of what I now know about LSTMs that is added to my long term memory is now approaching one. Thank you! I'm waiting, with great attention, for the transformer video!!!
Awesome! I'm glad to hear the video was helpful! :)
Attention is all you need 😃😃
@@otsogileonalepelo9610 :)
Im a native spanish speaker and when this video played speaking spanish my face was genuine horror, mainly because im used to josh’s voice. I’m glad i could switch it back
Ha! That's funny. Well, to be honest, one day my dream is to record my own Spanish overdubs. I'm still very far away from that dream coming true, but maybe one day it will happen.
I'm currently studying for my NLP exam. Sending all my gratitude from Italy for such a clear and in-depth explanation.
Good luck! BAM! :)
I swear to god I was searching videos about LSTM. I watched yours about Recurrent neural networks a few hours ago, but you didn't have any on LTSM. And now this is here!!! WTF?
Time to watch it then.
bam! :)
Amazingly explained! Can't wait to watch transformer!
Thank you! :)
BAAAM, First. Gotta Thank Professor Josh before I even watch the video
bam! :)
Excellent! StatQuest has explained XGB and DL mostly clearly I have ever seen. I can't wait for your new videos on attention and transformer.
Thank you!
Thank you very much! Complex, but clear
I think I will need to rewatch your videos to really understand and remember
Thanks!
great series of videos, please make some for "transformers" too!! Thanks in advance
I'm working on them.
Thanks so much! It is really the best tutorial! However, I do have a tiny problem. I really appreciate it if you could give me some help.
In 18:00, when using LSTM to predict company A, you said that the final short-term memory represents the predicted price on day 5. So, when you input the price on day 3 (which is 0.25), the short-term memory (which is -0.2) should represent the predicted price on day 4. However, the real price on day 4 is 1. There seems to be some problems.
In order to keep this example as simple as possible (so I could illustrate it), this model was only trained to predict the value on day 5. It wasn't trained to predict the value on day 3 or any other day.
Got it. Thanks for the swift and helpful reply! I'm truly grateful for your help and your tutorial!@@statquest
HOLY SMOKES the concept is now crystal clear 🔥🔥🔥🔥🔥
Hooray! :)
Truly a magical way of explaining such complex topics!
Thank you!
Didática impressionante. Vi várias vídeos e esse foi o que mais deixou claro.
Muito obrigado!
Thank you very much sir. I was hired as an undergraduate research assistant earlier this year, and took this opportunity to discover and learn about Deep Learning. I am currently learning about RNNs, and this video was of great value to me.
Thank you very much for this.
Glad it was helpful! :)
I am in Love with your videos!!!!
I was going through hell understanding LSTM but now I can say, I have some grasp🙌🙌
Hooray! I'm glad they are helpful.
It was the most easy explaination of LSTM ever, Thank You So Much...
Thanks!
Outstanding! Thank you for the LSTM video! It was of great help to me!
Great to hear!
So far the best explanantion for LSTM. Thanks a lot for this video. EAgerly waiting for the next stage 'Transformer'.
Thanks!
Wow! These videos are absolutely incredible! What a presentation!
Thank you!
Hands down the best explanation for LSTM!
Wow, thanks!
Agreed.
Man!.. This video is awesome! .All of your videos are awesome! You are awesome!!!
Glad you like them!
I have no clue why on earth such content is FREE!
bam! :)
The best explanation how LSTM cell works.
Thank you!
You are the best explaining! Thanks!
Glad you think so!
omg i am so fond of these videos! Thank you so much for doing it!
Thanks!
This was the best video about LSTMs that I've ever seen! Thanks!
Thank you! :)
Your tutorials are amazing. I wish you a good luck for your future. Thank you for making such an amazing tutorials 🙂
Glad you like them!
The best explanation on LSTM ever! Thank you so much!
Glad it was helpful!
@@statquest Thank you for your reply, Josh. One thing I am a little confused about is the difference between short term memory and prediction. At around 18:00 when you explain the day 5 prediction, you said that the final short term memory is day 5 prediction. Does that mean the input value is the actual price at a certain date and the short term memory is the price prediction at a certain date. If that's the case, then the short term memories should be very close to the input values but they are not (0, -0.1, -0.1 ,-0.2 vs 0, 0.25, 0.5, 1).
@@leejo5160 The model was only trained to predict the output on day 5. And, as such, only makes good predictions for day 5. However, we could train it to predict every day if we wanted to. We'd probably need more data or a more complicated model (more layers or a fully connected network at the end).
best explanation ever, i can't express how glad I am to found this channel. 100% better than the paid course I am doing right now. Thank you :).
Glad you enjoy it! :)
This what Teaching should be. I have tried watching a bunch of videos in youtube almost all of them were technical jargon. Didnt understand the why part!
Thank you Dr. Starmer for making such videos
Thank you!
Thank you you are the best teacher, I have seen. 🎉🎉🎉 Hurray. I learn from you than from my actual teachers who just waste my time and break my nerves down ....
Thank you 🙏🙏🙏🙏🙏🙏
I'm glad my videos are helpful! :)
Sir, this is my extremely awaited topic.A lot of Thanks. i know after watching LSTM my doubt will be clear.
BAM! :)
Probably the best and cleanest explanation of LSTM. Awesome!!. Could you please make a video on GRU?
I'll keep that in mind. However, right now I'm focusing more on attention and transformers.
Amazing explanation. It just cannot be better.
Glad you liked it!
Are these topics covered in "The StatQuest Illustrated Guide to Machine Learning"? The video is hands down the BEST explanation of LSTM I have seen anywhere!!!
The chapter on neural networks does not cover LSTMs. Just the basics + backpropagation.
@@statquest Would you consider a book explaining deep learning concepts? It would be a major life saver for all of us
@@amitpraseed I'm, slowly, working on one.
Crystal Clear. You're genius!
Thanks!
Thank you once again for a wonderful knowledge sharing and presentation. 🙂 TRIPLE BAM!!!
Thanks!
You are absolutely slept on. I love how you talk to me like I'm an idiot but sometimes I think you're just being nice.
These videos are just how I teach myself a topic. So, any tone is directed towards myself.
@@statquest totally joking it's an awesome vid
This is so funny because I was subscribed for a while and today thought “Hmm let me see if Statquest has a video on LSTM because I really need it.” And what do you know…
BAM! :)
I seldom comment on videos, but credit lies where it's due. Hands down the best video on LSTM I have watched
Thank you!
Very well illustrated, thank you!
Thank you!
Finally, I understand the mechanism. Thanks, Josh!
bam!
What an amazing video this was! Cannot wait for the transformers video. Keep up the great work!
Thank you! :)
Well done.. more than clearly explained... really its highly appreciated your hard and great work here... to easy understanding...🙏🙏
Thank you very much! :)
This channel is a blessing
Thank you! :)
Thank you so much for this, so well explained. MEGA BAM!
Glad you enjoyed it!
I am making a comment on a video after a really really long time. And for me this is the best criteria to show myself how useful this video is. Thanks :)
Thank you very much! :)
Very well explained; thank you so much!
Thank you!
Thanks for all of these great matrial. Your boook is also amazing!
Thank you very much! :)
Great explanation!!! Now I understand LTSM. Thanks a lot !!! 🙏
Thanks!
Thanks for sharing such great content!!! I bought your book and it is outstanding. Looking forward to seeing one video related to Gated Recurrent Unit too, it would be triple Bam :) !! Thanks Josh!!
Thank you so much for your support! BAM! :)
Really grateful for your dedication..Perfect video like always..Yet I missed the last part in which you revise the whole concept
I miss those parts too. But very few people watched them. :(
@@statquest 😥.. Those 2 mins are really helpfuk in grasping the essence of the complete video. Btw, I am glad I found your channel to make me understand the real stuff without getting confused in complex mathematical notations.