Mini Batch Gradient Descent | Deep Learning | with Stochastic Gradient Descent

[@MachineLearningWithJay]

If you found this video helpful, then hit the *_like_* button👍, and don't forget to *_subscribe_* ▶ to my channel as I upload a new Machine Learning Tutorial every week.

[@sumitsp01]

This is by far the best video on introduction to optimizers. Very precise, articulated and clears all the doubts. Thanks a lot brother !

[@MachineLearningWithJay]

Glad it helped you 😇

[@alexkonopatski429]

good video! but I have only one question: where does the noise come from, that you mentioned at 5:11?

[@MachineLearningWithJay]

Thats how the loss changes when we have more number of features

[@arvinflores5316]

Oh wow. When I was start learning ML, last year, your linear regression was one of the vids I first watched. Now, I'm a data scientist, you're still uploading high quality vids. Thank you! Hopefully we could get to see LSTMs and Transformers in the future. :P good day.

[@MachineLearningWithJay]

Wow... Really good to know this. Thank you for sharing your story! And Yes I will be uploading videos on LSTM.

[@arvinflores5316]

@@MachineLearningWithJay Wow nice! Can I make a suggestion? Maybe in the future you can include weight initialization like Xavier and He Norm. Those topics tend to be ignored because the computer is basically covering those, (I'm guilty of that :P) without knowing the reason behind it, e.g the disadvantages of weight initialization with 0 value.

[@MachineLearningWithJay]

@@arvinflores5316 Thank you for giving this suggestion. I will definitely consider making videos on these topics.

[@dr.ranjinips3103]

Very nice Explanation. Super

[@devanshsanghavi]

Brilliant explanation... Keep it up!

[@MachineLearningWithJay]

Thank you!

[@afn8370]

very good explanation. u need more views

[@harpbeat500]

great video

[@MachineLearningWithJay]

Glad it was helpful!

[@hardikdas2378]

very informative and precise.

[@MachineLearningWithJay]

Thank you!

[@AbhinavSingh-oq7dk]

So from what I understand, in Mini Batch Gradient Descent, model will train 1st mini batch, update the weights and then those updated weights will be used to train the 2nd mini batch, update and then the 3rd mini batch,..., till the last mini batch (1 epoch), then the last mini batch updated weight will be again used on 1st mini batch during 2nd epoch and so on? Do correct if wrong.

[@MachineLearningWithJay]

You are correct on your understanding Abhinav. I would just like to correct the words. You can say that the updated weights after training on any mini-batch is used to propoagate forward, and then they are updated again in backward propagation. Eg, randomly initialise weights at the beginning. Propagate forward (perform forward propagation) using 1st mini batch, then perform backward propagation, then update weights. Use those updated weights to perform forward propagation using 2nd minibatch, then backward propagation, update weights again and so on.

[@AbhinavSingh-oq7dk]

@@MachineLearningWithJay Thanks :)

[@amirrezamousavi5139]

Great job

[@MachineLearningWithJay]

Thank you!

[@choice_of_royals5268]

amzing, deeply explained. thanks

[@EEDNAGELIVINAYAKSHRINIWAS]

Your videos are helpful, Can you suggest a good book on same...

[@MachineLearningWithJay]

Hi... I don’t refer any book so can’t suggest you any. Although you can search for good books on ML online. I once found an article which showed top 10 books for learning ML.

[@EEDNAGELIVINAYAKSHRINIWAS]

@@MachineLearningWithJay Ok ! Thanks!...But have topics like batch normalisation and standard network like LeNet, AlexNet, AGG, GoogleNet in detail

[@MachineLearningWithJay]

@@EEDNAGELIVINAYAKSHRINIWAS Have you read the original research papers for these? I think you can learn about these in their research papers only.

[@EEDNAGELIVINAYAKSHRINIWAS]

@@MachineLearningWithJay Ok..can you mail me on my id lets discuss separately on some projects

[@MachineLearningWithJay]

Hi Vinayak, you can mail me on [e-mail] with your query. I will see what i can do to help.

[@GK-jw8bn]

very good explanation! well done!

[@MachineLearningWithJay]

Thank you!

[@chenmoasis]

Amazing helpful video!

[@malikhamza9286]

Amazing dude. Keep it up.

[@MachineLearningWithJay]

Thank You So Much !!

[@SaschaRobitzki]

Great job!

[@hosseinkarimi3381]

Thank you so much for your videos.

[@MachineLearningWithJay]

You're Welcome. Glad you like them! 😇

[@jordiwang]

you got a new sub bro, good video

[@sharangkulkarni1759]

ty

[@MachineLearningWithJay]

Welcome!

[@azadehazhdari931]

👌

[@mugomuiruri2313]

good boy