One of the best explanation ever on LSTM! Greetings from Politecnico di Milano!
@sonhdang3 жыл бұрын
I've watched dozen of videos on LSTM and this is the best one so far. Thank you so much sir. Greetings from UCLA!
@DigitalSreeni3 жыл бұрын
Glad it was helpful!
@pfever2 жыл бұрын
Best LSTM explanation I have watched! All your videos are superb! I want to watch them all from beginning to end! Thank you for such detailed and intuitive explanations! :D
@christophbrand90153 жыл бұрын
The first youtube tutorial I saw which explains a LSTM in detail, e.g. why a Sigmoid or why a tanh is used within the cell. Great!
@Balakrish-cl9kq2 жыл бұрын
I feel very gifted that I got the suggestion from KZfaq, the right video....
@DigitalSreeni2 жыл бұрын
I am glad you found my channel :)
@edwardbowora Жыл бұрын
Best teacher ever.
@DigitalSreeni Жыл бұрын
Thanks
@learn2know792 жыл бұрын
I was struggling to understand the basic concept of LSTM and watched dozen of videos and finally found the best one so far. Thank you so much for letting us understand. Greetings from GIST!
@DigitalSreeni2 жыл бұрын
Great to hear!
@saaddahmani1870 Жыл бұрын
Good, thanks a lot.
@DigitalSreeni Жыл бұрын
You are welcome
@AshishBamania952 жыл бұрын
Can't believe that this is free. Thanks a lot. You are building a community of future researchers and innovators here!
@DigitalSreeni2 жыл бұрын
My pleasure!
@user-fd9tv9fq8z4 ай бұрын
I get valuable Understanding. I realy appriciate the way of your explanation.
@mehdisdikiene87523 жыл бұрын
I've watched many videos and read a lot about LSTM but this is the first time i really understand how LSTM works. Thumbs up thank you!
@DigitalSreeni3 жыл бұрын
Great to hear!
@dizhang947 Жыл бұрын
amazing work, thank you so much!
@lh27382 жыл бұрын
Nice video, so well explained and not too long, along with a full tutorial. Probably one of the best ones about LSTM. Thanks and please keep up the good work! Greetings from France!
@yangfarhana36603 жыл бұрын
I've viewed several vids on LSTM but this breakdown is the best!!
@AhmedFazals4 ай бұрын
Awesome! Thanks sir.
@jahanzaibasgher12752 жыл бұрын
Thank you so much :) Subscribed after watching your first video.
@gadisaadamuofficial2946 Жыл бұрын
really, thank you for your more clarification!
@davidomarparedesparedes87183 ай бұрын
Great explanation! Thank you so much!! : )
@omniscienceisdead88372 жыл бұрын
Best explanation out there, i understood, what is happening both conceptually and mathematically
@claybowlproductions Жыл бұрын
Sir you are a gem!
@aristideirakoze80982 жыл бұрын
We are infinitely grateful
@DigitalSreeni2 жыл бұрын
Thank you :)
@Toss3geek9 ай бұрын
谢谢老师
@alteshaus31493 жыл бұрын
Thank you very much for this video sir!
@zhiyili67072 жыл бұрын
Thank you very much! It is well explained!
@s.e.72683 жыл бұрын
I am so happy to discover this channel! :)
@indranisen5877 Жыл бұрын
Thank you Sir, Nice explanations.
@kukuhiksanmusyahada76152 жыл бұрын
Great presentation sir! thank you so much!
@RAHUDAS2 жыл бұрын
At 19:31, he mentioned how many units of LSTM , the units parameters is not for how many units of LSTM in any layer, it is for hidden state dimension. And for how many LSTM depends on input shape[0].
@Droiduxx Жыл бұрын
So if I understand well, if we consider the input to be a sequence of x elements, each "LSTM" unit contains x states, and returns a list of x vectors passed to the LSTM units of the next hidden layer. Am I right ?
@RAHUDAS Жыл бұрын
@@Droiduxx yes, but consider return_sequence, and return_stae arguments also, their default values false , to see the full picture, kindly turn on return sequence. Example - x = tf.range(60) x = tf.reshape(x,(5,3,2)) # shape - ( batch, time, num-features) lstm = tf.Keras.Layes.LSTM( 7, return_sequence= True) Output = lstm(x) Print(Output.shape) # answer (5,3,7)
@gakhappy3 жыл бұрын
Great work sir. keep on doing great job
@-mle5662 жыл бұрын
thank you, nice video for LSTM new learners :)
@rolandosantos77553 жыл бұрын
i love your video...i am just starting to learn machine learning and its very useful'
@aminasgharisooreh92433 жыл бұрын
Thank you, it is really helpful
@DigitalSreeni3 жыл бұрын
You’re welcome.
@alex-beamslightchanal87432 жыл бұрын
Nice tutorial! Thank you!
@nisa_ssa3 жыл бұрын
Thank you so much for this video...
@jolittevillaruz52343 жыл бұрын
Very intuitive video!
@karamjeetsinghmakkar3323 Жыл бұрын
Dear Dr. S. Sreeni, Thanku for your informational videos regarding cnn. Kindly make LSTM for image classification tasks. Thanku.
@DigitalSreeni Жыл бұрын
LSTM is primarily used for processing sequential data. While it is possible to use LSTM for image classification tasks, it is generally not the best choice as it is designed to model sequential dependencies in data, whereas images are inherently spatial and do not have an obvious sequential structure. Images are typically processed using CNNs, which are specifically designed to handle spatial data and can effectively extract features from images using convolutions.
@VCodes3 жыл бұрын
great. thx a lot
@rahuliron16353 жыл бұрын
awesome explanation thank you very much
@DigitalSreeni3 жыл бұрын
Glad it was helpful!
@sadafmehdi29913 жыл бұрын
Nice Explanation Sir!
@cryptodude53592 жыл бұрын
Amazing tutorial! I got a question: At 14:59 you explain the forget gate. In the lower-left corner, the cell gets ht-1 (last timestep) as input. Is it possible to have a sequence of past days as input? For example ht-1 & ht-2 & ht-3 ... etc. to spot potential trends in the data. Maybe with multiple variables. Giving every single timestep an additional weight.
@dantec.dagandanan37322 жыл бұрын
Thanks!
@dantec.dagandanan37322 жыл бұрын
I know this little amount of money is not enough to say thank you. Keep the good works ser, 🥰
@DigitalSreeni2 жыл бұрын
Thank you very much. No amount of money is little. Every penny counts :) Bulk of the money goes to charities that help with cancer research and eye surgeries for poor people. So the society benefits from any amount that is contributed. Thanks again.
@manideepgupta24333 жыл бұрын
Amazing Sir.
@aomo5293 Жыл бұрын
Thank you, honestly it s very clear. Please I am looking for a tutorial on image classification but using local images dataset. Have y made a one before. Thank you again
@nicolamenga8943 Жыл бұрын
Thank you for the video. I have a question. The number of units (50) is the number of the so called "hidden units", also known as "hidden size"?
@awesome-ai1714 Жыл бұрын
11:40 What is going on with the arrows? Signal from previous cell merges with current Xt, but there is no operator. Signal from left and signal from bottom Xt. And they both go to 3 gates? Edit: ok I see, its explained later
@tchintchie3 жыл бұрын
I can´t help but find this channel incredibly undersubscribed!!!
@DigitalSreeni3 жыл бұрын
I’m glad you like the content. I rely on you guys to spread the word :)
@kanui36183 жыл бұрын
nice explanation!
@DigitalSreeni3 жыл бұрын
Thanks! 😃
@vzinko Жыл бұрын
Why is there a dropout after the final LSTM layer?
@ziyuelu17342 жыл бұрын
thanks!
@AveRegina_2 жыл бұрын
I'm using RNN for my PG thesis work. I've a query. Do we have to run stationarity test for our time series data before feeding it in the neural network model... or this step is only required in traditional time series models like ARIMA?
@DigitalSreeni2 жыл бұрын
RNNs are capable of learning nonlinearities (compared to ARIMA) and therefore should be able to learn from the input data without doing any stationarity pre-processing. This is especially true if you use LSTMs. Also, please note that you need lot more training data for RNNs compared to ARIMA. You may find this blog useful to understand the effectiveness of RNNs: karpathy.github.io/2015/05/21/rnn-effectiveness/
@sherrlynrasdas8387 Жыл бұрын
Can you teach us how to use LSTM and ARIMA in ensemble learning in forecasting time series data?
@hudaankara56163 жыл бұрын
Hi sir. thank you for much for all your videos. Could you provide us with tutorial to implement LSTM & RNN with Python Please?
@DigitalSreeni3 жыл бұрын
Yes... they should be out this week.
@stevenzhou73582 жыл бұрын
Thanks for your videos! It's really helpful. I have a small question. Could you explain a little more about the meaning of units? Is it mean the number of hidden layers or the number of neurons in a layer?
@DigitalSreeni2 жыл бұрын
May be this helps... stats.stackexchange.com/questions/241985/understanding-lstm-units-vs-cells
@stevenzhou73582 жыл бұрын
@@DigitalSreeni Thanks a lot! It's very helpful.
@JJGhostHunters Жыл бұрын
Hi DigitalSreeni...I am a PhD candidate investigating applications of MLPs, CNNs and LSTMs. I see that you have amazing graphics for these model types in your videos. Would you be willing to share these graphics for the model architectures with me so that I may use them in my dissertation and defense presentation? I certainly would give you credit for them. Thank you for your time!
@bobaktadjalli6516 Жыл бұрын
Hi, well explained! Could I have your slides?
@ramchandracheke3 жыл бұрын
First like a video then watch it !
@DigitalSreeni3 жыл бұрын
Thanks for your blind confidence in the video, I hope your opinion doesn’t change after watching the video :)
@aminasgharisooreh92433 жыл бұрын
please make a video about attention in images
@DigitalSreeni3 жыл бұрын
I got your attention :)
@XX-vu5jo3 жыл бұрын
Lol ever heard of transformers???
@DigitalSreeni3 жыл бұрын
Now sure what your meant by your comment, was that a question?
@pattiknuth48223 жыл бұрын
His continuing use of "ok?" "ok?" "ok?" "ok?" is incredibly annoying.
@adhoc30183 жыл бұрын
And you are not annoying at all.
@DigitalSreeni3 жыл бұрын
Poor choice to comment on personal trait rather than content of the tutorial, ok?