Fool-proof RNN explanation | What are RNNs, how do they work?
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- Опубликовано: 5 авг 2024
- Recurrent Neural Networks and their variants have been the superstars of AI in the last couple of years. But how do they work under the hood? What is their structure like? How do they learn? In this video, we will answer all of those questions, step-by-step. We will first see the difference between neural networks and recurrent neural networks. We will also look into types of RNN cells such as Simple RNN cells, LSTMs and GRU cells.
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there are several contents on RNN which does not explain the intuition but yours is the best content i've seen which gives you the intuition and concepts in a short video thanks a lot
In only 3 minutes, I understood the concept that I couldn't understand in hours of lectures. Good Girl!
Hope this explanation was helpful for you! Did you hear anything for the first time in this video?
Ahh this is exactly what I needed! Thank you so much for explaining RNNs in such a clear way :) Keep up the great work - I'm sure it's much appreciated by lots of viewers!
That’s great to hear Christina! I’m glad it was helpful. :)
Very intuitive explanation, espeically with your interpretation! Keep up the great work :)
High quality content and very well explained. I saw about 10 different videos of RNN and by far this is the best. thanks a lot!
That's great to hear, thank you!
Very clear description, thank you!
crystal clear explaination of RNN !!! Thank You so much ❣
Thank you. This was precisely the explanation I was looking for: especially how the input is handled in terms of time-steps..
You're very welcome!
Amazing Explanation!! 👏
Awesome video!!! Eagerly waiting for the next one on this channel :)
Thank you Python Engineer!
That's a very important topic. This video inspires me to add RNN to my code demonstration library. Thanks.
Awesome to hear!
Wow! You explained this so much better than Lex Fridman :D
So easy to understand
Hello Misra 🙂🌻 Thank you so much for concise summary on RNN and variants 🎉
You are very welcome. :)
Thank you for sharing this.
Thank you for your amazing explanations ! I have now a better understanding of LSTM thanks to you clarity.
That's great to hear Jérémy!
thats so clear explanation! It would be awesome to give a real example with sequential data where you have vectors with the weights.
Good explanation.
you are doing awesome job, thank you !
Thanks Tech Elefant!
Very well and clearly explained. Thanks
You're welcome!
This is awesome! Thank you!!
Thanks! and you are very welcome :)
Highly Underrated Channel. Just one thing to ask how many layers are there in each RNN as you wrote weight matrices are all same since its actually only one cell. Also when then input from last timestamp comes how is it simultaneously passed along with other input. Are both vectors added ?
this tutorial is fire
Explanation is fine. Only one wish is to make some insulation in the studio to avoid big echo
Very Good explained
Thanks!
I read the title and thought: "Fool-proof? Well, I'm a fool! I better watch this!"
WE MAKING IT OUTTA THE AGI WITH THIS ONE🗣🗣🗣🗣💯💯💯💯🔥🔥🔥🔥
hi there, may I ask if RNN (particularly LSTM) can be trained as any NN for both classification and detection? like can I classify action and detect say face ?
Your video just proved me a fool. I now understand it
thanks
You're very welcome!
Hi, thanks for your helpful videos, you are very smart and beautiful.
Great to hear you like the videos!
I am from india i am in 10th grade i know little python i wanna become a data scientist can i take this course? On your website in this your official website i hope?? Please give me a reply?
Hey Mike, yes the link in the description is my official website. :)
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Thank you!!