RNN and Sequence model uses: 1. Completing Sentences 2. Translating Sentences 3. Entity Recognition 4. Sentiment Analysis Sequence is important here N.N work on numbers not strings so you will have to apply Hot-Encoding
When I do NLP processing now, I apply a Lisp or Prolog based approach where one matches everything at once. Years ago I learned that to understand a sentence, one must know the words, and to know the words, one must know the sentence. So the approach is to look at the whole sentence, and process the words and the sentence at the same time and as each part is discovered or combined, they reinforce the others. Nice video ----
@@codebasics its the ole 22 phrase, one cannot get a job without experience, so how do I get experience without a job" ----- you process both simultaneously from front to back, back to front, and the middle in between, as each word is identified, the phrase becomes identified, yet the phrase cannot be identified until the word is identified" Do multiple threading on the sentence at the same time, while continually combining into the largest sections and to the most discrete sections and bubble up and bubble down - bottom up, top down, meet somewhere in the middle where all parts agree ----------- so simple in an analogy ----- so now I code it once again :-)
00:03 Recurrent Neural Network (RNN) is used for natural language processing tasks. 02:02 RNN is used for sequence modeling in language translation. 03:59 One hot encoding simplifies word representation 05:53 Sequence is crucial in certain tasks 08:02 Recurrent Neural Network (RNN) processes words word by word and carries context or memory. 09:51 Recurrent Neural Network (RNN) uses time travel to process sequential inputs. 11:54 Recurrent Neural Network (RNN) processes input in a loop 14:04 RNN allows for sequential processing of input data for tasks like language translation and requires all words to be supplied for translation. Crafted by Merlin AI.
Your videos are so simple and easy to understand. They get across the basic intuition of Algorithms with ease. It's been challenging for a me to get in to this field and this content has been really helpful for me.
It was pretty awesome, I have understood the RNN from your explanation and wondering about the word "Recurrent". And telling myself, ohhhh, that's why it's called Recurrent Neural Network.
Thanks, I finally understand RNN. So basically you first encode each words in your sentence then feed encoded vector with weight to the neural network with activation function. Afterwards you feed next encoded vector with weight feed into neural network until feed all the words. So it’s like a loop, we only using on neural network. That a important point. And then we calculate the loss and use back propagation to adjust the weight and bias in our network.
this is brilliant, your explanation truly helps one build a genuine intuition for concepts. found your channel trying to understand whether USE or BERT would be better for my use case, so happy that I did
Thank you very much for this wonderful and simple explanation on RNN. I finally understood the concept. Lots of love from Saudi Arabia...Keep going. You are a genius.😃👍
This is my firstv video in ai or deep leanring, but clearly understood, tq for the clear cut explaination, by seeing your video i am very curious to explore this field of ai and deep learning, thank you.
you are a great man , thunk you for all what you did and what you are doing and what you wild do , you make deep learning looking like a simple math operation (1+1=2) , i encourage you to continue in this path of teaching
Amazing. Sir, you may not be aware how easy you are making it. How close you are taking us to application. You must be taking huge efforts to make it so.
Hy bro, u r really awsmm. I don't really understand the class, explained by my professor. before going to the class, i will go through ur tutorials. it really helps me to understand well. thank you bro
thank u so much, expecting next topic videos in sequence, like LSTM,Bi-LSTM,GAN, please do videos with one example classification task like hate speech detection with these concepts like RNN, LSTM?
Hi, I have a doubt at at timestamp 09:00 in the video. In the NER example, for the input vector which one-hot encoding, for each word like Dhaval loves baby - there are 1's at two different places in the vector. Being one-hot encoded there should be only one '1' in each of the vectors right? This 1 corresponding to where the word appears in the vocab. Please clarify? Krish
Hello. The ground truth 1 0 1 1 is the y(answer). The network input is a word vocabulary( could be hot encoded or word embedding ). Each word has your unique vector
At 13:20 , it was mentioned to adjust weights after pass each sentence, while i remember in ANN the weights are adjusted after one epoch. Am I mistaken?
Hi. Thanks a lot for this explanation on RNNs. I had one question. At 4:25, you mention that converting the sentences to vector is called one hot encoding. Isn't it bag of word transformation? I request a clarification about this doubt. Thanks.
Thanks for the easy and simple explanation ! I just have a question: around 3:49 and about the issue #2, you were talking about the one hot-encoding issue that results in high computation cost in MLP. How does RNN solve this issue? and how are words represented in RNN if not in hot-encoded binary format?
Sir! Most of the time, I have seen We predicting only number values from our Machine Learning Model. But I want know that How to find Category Values by taking Number values. Such as If I have a model that can predict a list of shop that giving Min price X and max price Y.
You asked an interesting question Himalay. We need to think about few things (1) is your base for output the current price meaning based on current prices from different shops you want to input a product and find shops between price x and y? That wouldn't be a machine learning problem, you can simply to price comparison using SQL query (2) Say based on some features we are trying to predict future price from different shops, in this case one option is to build separate model for each shop and train them. When you are ready for prediction you get predicted output for each shop and now do your price comparison for min x and min y. There is also multioutput regression which can predict multiple outputs, need to see exact problem statement, features to see if that can be utilized: machinelearningmastery.com/multi-output-regression-models-with-python/
@@codebasics Sorry, Sir. But I think you couldn't understand. I checked out your Real Estate project of Banglore city. It is giving prediction prices based on a few categories such as location, BHK, Bath, etc right? But If I want to location such as Akshay Nagar etc by giving Area, My budget as Estimate price and more. So I want to predict string Category, not number or int. Then what can do about it?
@@hp6hp1 , Neural network do not predict string as output directly. But they do predict word vectors or give probability distribution as output. We need to decode these output to get the respective output
Hi Sir, at 13.36, what will be the value of Y^(hat) at the first layer(Ironman)? Will it be 1 or [1 0 0 0] , asking this question as we are only passing oneword to the first layer.
Sir, I need one advice. Have a job offer of data analyst, shall I take it and later move to data science and machine learning field or keep searching for machine learning related jobs? I wish I could have a word with you on chat/email.
Depends on your situation... are you in need of earning money immidiately if yes then take it. you can move to ML job later on as well but your experience as a data analyst might (or might not) create some hurdles for you in future. whereas if you start as a data scientist from your first job itself your resume would look clean
Thank you sir.. I just have one query..we can use Feed forward NN for sentiment analysis and there also sequence of the words matters.. then how does that NN deal with that?
Your videos are very informative and simple, but one thing you mentioned RNNs are sequence models but translation would not be always sequential when we translate an English sentence to French or Spanish, words may be here and there then RNNs would not work as efficiently. Is there any other model we can use??
When you explain classifying is transaction fraud or not Sequence wasn't important but I think in real process in ANN input node has also label right? then if the input datas' sequence is different from before Consequently layer's weights were also changed. ( ex) input [1,2,3] and [3,2,1] bring about different output in ANN too. so I could say this model has sequence too!) Am I wrongly understand ANN? plz help me THANKS :)
yeah, this guy make a mistake . changing the sequence for ANN also give different output since changing sequence mean you put different vector value to each node which has different bias and weight .the thing is Neural network is also can used for NLP as long as it wasnt a complex sequence , and also even simple RNN cant be used for complex sequence too.. usually we using RNN-LSTM for complex sequence. hope this answer help you
What does these functions in figure.canvas do? What is figure.canvas? fig.canvas.draw() fig.canvas.get_width_height() fig.canvas.tostring_rgb() What is fig.canvas if you could explain in detail. Also what does this code do: `image = np.frombuffer(fig.canvas.tostring_rgb())’ I tried hard but could not get any documentation related to them. Are they obsolete? Please help me I’m stuck
Finally I found you very luckily. Please resolve my query. I am newbie in python. So I want to finish only python basic then I want to move ML and want to complete all ML course with Python. Should I move to with Python basic only? I believe I will get satisfaction ans from you only.
sure. you should follow my first 15 videos in my python tutorials playlist and then first 9 videos in pandas playlist. After that you can directly jump to my machine learning playlist.
@@codebasics i have follow you always and i remember you are a very good guidance for us. Really this is great and valid information for me. so first 15 videos for python and first 9 videos for pandas this is fine to move your machine learning course. I mean no need anything to without this for begging to expert ML learn....... please let me
Sir was planning to do data analysis course according to your 3months plan wanted to know that i can do that course with any basic laptop of 4gb ram, i3 intel or i need much higher configuration laptop? (I'm asking about each and every tools which i have to learn)
Sir can u running an institute I want to learn data scientist I have done my graduation in commerce if no Then give me a one suggestion which institute is best for to learn data scientist
See I request you to use analogy which everyone in India understands. In this video , the analogy is hindi words not understanding for us students of southern India. @codebasics you have fans throughout India but expecting respect for everyone equally
Check out our premium machine learning course with 2 Industry projects: codebasics.io/courses/machine-learning-for-data-science-beginners-to-advanced
I don't want to go in NLP can i avoid this ahead videos, because I have to focus on computer vision.
Saw like 3-4 videos, no one really addressed that there is only one layer that is going through this process. By far the most clear video, thank you!
RNN and Sequence model uses:
1. Completing Sentences
2. Translating Sentences
3. Entity Recognition
4. Sentiment Analysis
Sequence is important here
N.N work on numbers not strings so you will have to apply Hot-Encoding
I am still new in this. Trying to follow up all your videos. You've got good explanation. Thank you.
👍👍☺️
When I do NLP processing now, I apply a Lisp or Prolog based approach where one matches everything at once. Years ago I learned that to understand a sentence, one must know the words, and to know the words, one must know the sentence. So the approach is to look at the whole sentence, and process the words and the sentence at the same time and as each part is discovered or combined, they reinforce the others. Nice video ----
👍🏼👍🏼👍🏼
@@codebasics its the ole 22 phrase, one cannot get a job without experience, so how do I get experience without a job" ----- you process both simultaneously from front to back, back to front, and the middle in between, as each word is identified, the phrase becomes identified, yet the phrase cannot be identified until the word is identified" Do multiple threading on the sentence at the same time, while continually combining into the largest sections and to the most discrete sections and bubble up and bubble down - bottom up, top down, meet somewhere in the middle where all parts agree ----------- so simple in an analogy ----- so now I code it once again :-)
00:03 Recurrent Neural Network (RNN) is used for natural language processing tasks.
02:02 RNN is used for sequence modeling in language translation.
03:59 One hot encoding simplifies word representation
05:53 Sequence is crucial in certain tasks
08:02 Recurrent Neural Network (RNN) processes words word by word and carries context or memory.
09:51 Recurrent Neural Network (RNN) uses time travel to process sequential inputs.
11:54 Recurrent Neural Network (RNN) processes input in a loop
14:04 RNN allows for sequential processing of input data for tasks like language translation and requires all words to be supplied for translation.
Crafted by Merlin AI.
Your videos are so simple and easy to understand. They get across the basic intuition of Algorithms with ease. It's been challenging for a me to get in to this field and this content has been really helpful for me.
Glad you like them!
It was pretty awesome, I have understood the RNN from your explanation and wondering about the word "Recurrent".
And telling myself, ohhhh, that's why it's called Recurrent Neural Network.
Glad you liked it!
Your explanation on recurrent neural networks is the best I've seen to date.
Thanks, I finally understand RNN. So basically you first encode each words in your sentence then feed encoded vector with weight to the neural network with activation function. Afterwards you feed next encoded vector with weight feed into neural network until feed all the words. So it’s like a loop, we only using on neural network. That a important point. And then we calculate the loss and use back propagation to adjust the weight and bias in our network.
this is brilliant, your explanation truly helps one build a genuine intuition for concepts. found your channel trying to understand whether USE or BERT would be better for my use case, so happy that I did
Thank you very much for this wonderful and simple explanation on RNN. I finally understood the concept. Lots of love from Saudi Arabia...Keep going. You are a genius.😃👍
Most welcome!
This is probably the best channel for students learning AI
Thanks a lot
Glad it was helpful!
Best video i have seen till now about basic understanding of RNN
Thank you
This is my firstv video in ai or deep leanring, but clearly understood, tq for the clear cut explaination, by seeing your video i am very curious to explore this field of ai and deep learning, thank you.
Superb video !!!....in fact most of the videos of this channel are amazing !!!!
Glad you like them!
you are a great man , thunk you for all what you did and what you are doing and what you wild do , you make deep learning looking like a simple math operation (1+1=2) , i encourage you to continue in this path of teaching
Seconded! What a guy!
Amazing. Sir, you may not be aware how easy you are making it. How close you are taking us to application. You must be taking huge efforts to make it so.
Thanks zanwardr for your feedback
Simply you're the best man hands down!!!
Thank you so much for your kind words.
dude,where you have been all this time?!Great video!! Finally got a pure and exact explanation of ML models!!
You are a great teacher! Very easy to understand explanation about RNN!
Keep these coming! Loving them.
😊👍
Hy bro, u r really awsmm. I don't really understand the class, explained by my professor. before going to the class, i will go through ur tutorials. it really helps me to understand well. thank you bro
Your explanation is so clear. Thankss for the video. I am new in this topic, so this video helped me a lot :)
I was waiting for this.
Your way to teaching is amazing!
Happy Teachers day.. u r doing a great job .. 👏
great job taking your time explaining those notions thank you!
FINALLY........😍😍😍
waiting for LSTM too...
yes LSTM will come up soon
Very crisp and to the point.Excellent explanation
thank u so much, expecting next topic videos in sequence,
like LSTM,Bi-LSTM,GAN,
please do videos with one example classification task like hate speech detection with these concepts like RNN, LSTM?
Raju, point noted. I will be adding all those videos that you suggested.
@@codebasics
How to do RNN with Sequential layers
you explain so crystal clear , not on the face of it.
Nicely explained. I came back online just to give a thumbs up and subscribe. lol.
Really awesome and simple explanation of RNN
Very good and clear. Thank you, Dhaval.
Very very cool video! I discovered right now your channel and it seems very promising
Nice explanation of RNN !!!
Well explained, better than tensorflow zero to hero
So well explained. Thank you!
Glad it was helpful!
Wonderful explanation...made it very simple
Glad it helped
Outstanding, keep the good work. thanks for the video.
Glad it was helpful!
Thanks a million for all super simple videos. God bless!
Hi,
I have a doubt at at timestamp 09:00 in the video. In the NER example, for the input vector which one-hot encoding, for each word like Dhaval loves baby - there are 1's at two different places in the vector. Being one-hot encoded there should be only one '1' in each of the vectors right? This 1 corresponding to where the word appears in the vocab. Please clarify? Krish
Hello. The ground truth 1 0 1 1 is the y(answer). The network input is a word vocabulary( could be hot encoded or word embedding ). Each word has your unique vector
Hi Dhaval ji,
This is just amazing! Your insight into concepts of RNN and all deep learning is unparalleled. Just great. Thanks from Krish
At 13:20 , it was mentioned to adjust weights after pass each sentence, while i remember in ANN the weights are adjusted after one epoch. Am I mistaken?
Thanks for amazing Video with simple explanation :)
Благодарю, связка рабочая.
Great Explanation
Glad it was helpful!
Amazing!
Nicely Explained
Thank you so much for the amazing videos!!
Glad you like them!
I am waiting for.it..please do a video about LSTM soon.
yup LSTM will come soon
Hi. Thanks a lot for this explanation on RNNs. I had one question. At 4:25, you mention that converting the sentences to vector is called one hot encoding. Isn't it bag of word transformation? I request a clarification about this doubt. Thanks.
converting text sentences into vectors by Bag of words technique.
Nine explanation sir...
thank you so so so much, Sir
Good job. Thank you, Sir!
👍😊
Thanks for the easy and simple explanation ! I just have a question: around 3:49 and about the issue #2, you were talking about the one hot-encoding issue that results in high computation cost in MLP. How does RNN solve this issue? and how are words represented in RNN if not in hot-encoded binary format?
which is best for forecating or prediction ... LSTM?
Sir! Most of the time, I have seen We predicting only number values from our Machine Learning Model. But I want know that How to find Category Values by taking Number values. Such as If I have a model that can predict a list of shop that giving Min price X and max price Y.
You asked an interesting question Himalay. We need to think about few things (1) is your base for output the current price meaning based on current prices from different shops you want to input a product and find shops between price x and y? That wouldn't be a machine learning problem, you can simply to price comparison using SQL query (2) Say based on some features we are trying to predict future price from different shops, in this case one option is to build separate model for each shop and train them. When you are ready for prediction you get predicted output for each shop and now do your price comparison for min x and min y. There is also multioutput regression which can predict multiple outputs, need to see exact problem statement, features to see if that can be utilized: machinelearningmastery.com/multi-output-regression-models-with-python/
@@codebasics Sorry, Sir. But I think you couldn't understand. I checked out your Real Estate project of Banglore city. It is giving prediction prices based on a few categories such as location, BHK, Bath, etc right? But If I want to location such as Akshay Nagar etc by giving Area, My budget as Estimate price and more. So I want to predict string Category, not number or int. Then what can do about it?
@@hp6hp1 ,
Neural network do not predict string as output directly. But they do predict word vectors or give probability distribution as output.
We need to decode these output to get the respective output
You are How . As a indian it makes sense to me
Thank You!!!!
Sir, do we must to add weights and bias?
Sir i have tried everything on the internet but my tensorflow isnt detecting my gpu and runs on cpu instead. What do i do?
Hi Sir, at 13.36, what will be the value of Y^(hat) at the first layer(Ironman)? Will it be 1 or [1 0 0 0] , asking this question as we are only passing oneword to the first layer.
codebasics
Please answer this question
May the Force be with you and Grogu.
Waiting for Friday's Bad Batch Ep 3.
Sir, I need one advice.
Have a job offer of data analyst, shall I take it and later move to data science and machine learning field or keep searching for machine learning related jobs?
I wish I could have a word with you on chat/email.
Depends on your situation... are you in need of earning money immidiately if yes then take it. you can move to ML job later on as well but your experience as a data analyst might (or might not) create some hurdles for you in future. whereas if you start as a data scientist from your first job itself your resume would look clean
Playlist is not opening 😅
are you clicking on a link in video description? It opens fine for me
Thank you sir.. I just have one query..we can use Feed forward NN for sentiment analysis and there also sequence of the words matters.. then how does that NN deal with that?
if possible can you give us notes on this series
For tumour detection RNN is suitable sir?
great way of explaining things ☺you should be teaching at university
Your videos are very informative and simple, but one thing you mentioned RNNs are sequence models but translation would not be always sequential when we translate an English sentence to French or Spanish, words may be here and there then RNNs would not work as efficiently. Is there any other model we can use??
sir how can i apply rnn for OCR? i want to build code recognition from image ? any tips and advice? im new to AI
Sir, you have used hidden layer at different states. I had a doubt does the size of hidden layer remain same at each state
Is Elman Recurrent NN or Simple Recurrent NN anonyms to each other or they r different in theory?
When you explain classifying is transaction fraud or not Sequence wasn't important but I think in real process in ANN input node has also label right? then if the input datas' sequence is different from before Consequently layer's weights were also changed.
( ex) input [1,2,3] and [3,2,1] bring about different output in ANN too. so I could say this model has sequence too!)
Am I wrongly understand ANN?
plz help me THANKS :)
yeah, this guy make a mistake . changing the sequence for ANN also give different output since changing sequence mean you put different vector value to each node which has different bias and weight .the thing is Neural network is also can used for NLP as long as it wasnt a complex sequence , and also even simple RNN cant be used for complex sequence too.. usually we using RNN-LSTM for complex sequence. hope this answer help you
@@VinVin21969 thx :)
38 like & 300 viewer it's not my mistaken cz I didn't get any notification from UA-cam.
Please make more videos on NLP !!
What does these functions in figure.canvas do? What is figure.canvas?
fig.canvas.draw()
fig.canvas.get_width_height()
fig.canvas.tostring_rgb()
What is fig.canvas if you could explain in detail. Also what does this code do:
`image = np.frombuffer(fig.canvas.tostring_rgb())’
I tried hard but could not get any documentation related to them. Are they obsolete?
Please help me I’m stuck
Finally I found you very luckily. Please resolve my query. I am newbie in python. So I want to finish only python basic then I want to move ML and want to complete all ML course with Python. Should I move to with Python basic only? I believe I will get satisfaction ans from you only.
sure. you should follow my first 15 videos in my python tutorials playlist and then first 9 videos in pandas playlist. After that you can directly jump to my machine learning playlist.
@@codebasics i have follow you always and i remember you are a very good guidance for us. Really this is great and valid information for me. so first 15 videos for python and first 9 videos for pandas this is fine to move your machine learning course. I mean no need anything to without this for begging to expert ML learn....... please let me
Sir Can you share the Ha
nd written notes..
gawd work
Sir u r like doctor with out pain u give injection which will clear our confusion.
ha ha.. thanks shaik for your very poetic, analogy based appreciation and feedback. It is always a pleasure to read your comments my friend :)
Sir was planning to do data analysis course according to your 3months plan wanted to know that i can do that course with any basic laptop of 4gb ram, i3 intel or i need much higher configuration laptop? (I'm asking about each and every tools which i have to learn)
I think it should be okay. I have not tried BI tools on such configuration so it is something you need to try an you will figure it out yourself
Sir, can you please make a video on word2vec technique 🙏
Sir can u running an institute
I want to learn data scientist
I have done my graduation in commerce if no
Then give me a one suggestion which institute is best for to learn data scientist
Kindly provide the slides
Thanks
Audio classification please 🙏
yes that will come up as well
@@codebasics thank you sir waiting for that
See I request you to use analogy which everyone in India understands. In this video , the analogy is hindi words not understanding for us students of southern India. @codebasics you have fans throughout India but expecting respect for everyone equally
Where is slides?
i need slides.
im struggling to understand what multiple neurons are doing here ... shouldnt we just need one neuron to do all this
07:46:00
Bitcoin mining with Actuall Bitcoin ecosystem please
okay point noted
Please sir make a video on nlp
A dedicated NLP tutorial series is coming up soon
"Tensorflow, Keras & Python"
where are they in your video?
although you explained the concepts nicely but please don't mislead people from next time
Why arabic translat can not
nice clarification
wait, is your name Dhaval?
sir, can you please explain the math needed for learning data structure and algorithm?
Golgappa 😋😋