244 - What are embedding layers in keras?

Code generated in the video can be downloaded from here:
github.com/bnsreenu/python_fo...
Embedding layer...
Maps each value in the input array to a vector of a defined size.​
The weights in this layer are learned during the training process.​
Initialization is performed (just like other keras layers).​
One-hot encoding is inefficient as most indices are zero. (e.g., Text with 1000 words means most of the elements are 0) ​
Integer encoding does not reflect the relationship between words. ​
Embedding allows for the representation of similar words with similar encoding.​
Values are learned (trainable).​

[@DataTranslator]

I am glad you clarified that the numbers show in the embedding are just the initial values and that we need to train the model to get the optimized embeddings

[@jayp9158]

Hands down one of the best explanations that I've seen not only for Embeddings, but for Machine Learning stuff. Thanks for this, I just subscribed.

[@DigitalSreeni]

You're very welcome!

[@firasbaklouti4017]

Hello Prof. Sreeni, just wanted to say thanks for taking the time to make videos to explain concepts and going through practical examples to see how the methods are used.

[@DigitalSreeni]

You are most welcome

[@payalkundu8492]

combination of intution + technical explanation in each video helping me alot to understand NN and solve my project,thank you for all these videos,feeling is quite similar to binge watching series,watching 3-4 videos at minimum/day

[@DigitalSreeni]

Glad to hear that. I like the binge watching part. The last time I binge watched something was during the Christmas break. I watched Squid Game, time well spent :)

[@joafin19]

I did not know what vector meant at first but after finishing the video through example code, it became clear. Thank you.

[@MARTIN-101]

by vector he means an array.

[@WahranRai]

One good example of word embedding is the code RGB of colors. Black = (0, 0, 0) ; Red =(255, 0, 0) ; Maroon =(128, 0, 0); Yellow=(255, 255, 0) etc...

[@MARTIN-101]

how so, what is the relation between rgb and embeddings ?

[@mithitagadiya278]

Perfect time of the video, I just started document classifying using Keras, I watched this video to understand embedding layers. Thank you.

[@DigitalSreeni]

Wonderful!

[@user-up5yw5zh5t]

both technical and theoritical is well explained, thank you sir

[@hessame9496]

Such a great job! Appreciate the quality of your videos!

[@DigitalSreeni]

Thank you :)

[@taha3871]

Great work, basic explanation of the concept! It genuinely helped me, but I wish you also talked about Collaborative Filtering Based Recommender Systems. With that, it might have been super helpful for my project, but thanks anyway!

[@shreyanshpandey8699]

Precise and Great Explanation

[@zahidinfovlog2419]

Hello professor, First i would like to thank you for the nice explanation. Actually in my project i want to use Keras Embedding Layer for the vectorization and i have to prove the committee that it can be a better option than the traditional methods such as one hot, Bag of words and TFIDF. I have tried too much to find a research paper on it that i can mention in my literature review but unfortunately i am unable to find. Please help me in this situation. I am very confused. Pleaee reply as soon as possible. Thanks

[@atangens11]

Great explanation! Thank you!

[@LearningWithNisa]

thank you so much for wonderful explaination. i always wonder about numbers assigned to each vector that how they are assigned, today i am clarified by watch this tutorial. Good job.

[@MichaelTrigoboff]

Very helpful. Thanks!

[@adachoudhry5523]

This was really helpful! Thanks:)

[@DigitalSreeni]

Glad it was helpful!

[@iseedrunkpeople00]

thanks for the explanation

[@response2u]

Thank you sir!

[@ishantguleria870]

very nicely explained

[@youssefasham1724]

Hi, thank you so much for this video. Is it possible to also use conditional GAN if the additional parameter is unbounded? For instance, is it possible to use conditional GAN to generate an circle image and the additional information is the radius (because the radius can be any value)?

[@mohamedikbalguetout32]

I want just to know how can I use embedding in machine learning models such as gradient boosting classifier or something like that? Any help please

[@danyellacarvalho4120]

thank you, sir!!

[@DigitalSreeni]

You are welcome!

[@withlove8876]

input_length should be set to 6 or the number of words in the input vector should be decreased to 5 else it will throw error.

[@alankruthisaieni2562]

Could u also include code for converting words to integers instead of taking array of integers directly?? Like how to build vocabulary and assign integers to words?

[@cplusplus-python]

Dear Professor, How we can get involved with data preparation? Lets say customized dataset for c-GAN. I mean is there any way we could get in touch? no more CIFAR-10 or MNIST.

[@StevenSmith68828]

I’m getting a little too deep with this. So I’m making a model that takes in y finance data to predict a price I was successful in creating a CNN for time series forecasting. I ran into a problem where my CNN MSE was not improving so I looked into a gated architecture I’m TRYING to create a variation of a ResNET where the convolution layer uses 1D Convolution and wanted it to feed Historical data with categories and data. Would this layer be added in conjunction with numerical data or maybe a separate branch.

[@musesafayigatalo]

Thank this tutorial is very helpful us ,but is there spell checker for any language project?

[@musesafayigatalo]

using deep learning i mean?

[@pranabsahoo1952]

Please cover capsule network

[@elizabethm.j139]

Dear sir, if my data looks like this then how to give embedding or how to feed a sequential model? 3,3,1,1,1,1,1,1,1,6,6,6,2,16,16,16,8,8,8,8,8,2,4,4,4,4,1,1,1,1

[@MARTIN-101]

have you encoded the words with thier respect unique ID ?

[@yashbharadwaj5468]

can u tell me how to deploy this model on android device

[@DigitalSreeni]

I've done a few videos on web deployment of trained models. Please watch my videos 268 to 271.

[@iseedrunkpeople00]

tell me more though

[@juliocardenas4485]

But you never trained a model

[@knowledgedoctor3849]

You are Great Sir, Love From KNOWLEDGE DOCTOR KZbin Channel. Wanna to connect you through mail. Thanks Advance