Thanks a lot for the content. One small request. Can you pls reduce the background music volume next time?

Very interesting! Thank you so much! :)

I am totally new to machine learning. From where do I start?

Thanks , how can we use VGG for 1D signal? Is it possible to use VGG for regression instead of classification, how?

very cool thank you for the knowledge

Glorious😳

Hey, fyi I had to reshoot some of the section on this video because I couldn’t stop saying Drop Path (from Fractal Net) instead of Stochastic Depth. There is still 1 wrong mention of drop path in there that I wasn’t able to fix haha That's what you get from reading two paper simultaneously!😅

thank you very much for your nice work can i have your slides?

Thank you! Exactly what I needed.

Nice work, but why was the first file overall a larger file to start? Character quantity?

Amazing video! Thanks!

Who the heck is Tanimoto

This is SUPER helpful. I was looking online for a good example using sklearn to no avail. Even asked ChatGPT and was led astray.

Thank you! this was exactly the explanation I needed

Will please tell me how to do ndam optimization in matlab for deep learning

thank you so much it helped me in project lot

can you give me the link to the exact jupyter notebook? I can't find the exact same jupyter notebook from the link that you provide on the description

Math.pow(2, x) is not how you square a number (saw it in your github).

Appreciate it man thank you. This is golden.

Thank you for your concise and clear explanation!

If I'm not mistaken you only return the entropy for the last checked nucleotide: entropy = 0 for nucleotide in {'A', 'T', 'G', 'C', 'N'}: rel_freq = dna_sequence.count(nucleotide) / len(dna_sequence) if rel_freq > 0: entropy = entropy - (rel_freq * math.log(rel_freq, 2)) return entropy

hi

This is a great project for beginners, thanks for this valuable information !

Hi, can you share example on fine and gray modeling? Also, where I can get these codes? thanks!

promo sm

Love this video !

Where are you from?

Keep going 💪💖

Welcome back

You're back again! That's amazing ✨

Can you please help me with rainfall problem with deepxde and physics informed neural network

So for nesterov gradient, the learning rate would have to be set constant and not found automatically using line search for each iteration?

Great video. Thank you

Great video. Thank you

Very helpful. Thanks!

Nice tutorial, thanks a lot. But! If you explain something - just explain. Watching how you was moving the pieces of code was so annoying!

i'm so frustrated that i don't know *hope i can learn to code math formulas in future* if anyone got some guidance please give

thank you very much for the tutorials and code! But I don't quite understand why both AdaGrad and AdaDelta perform poorly for these examples?

Great video. Thank you

Massa!! 👏🏽👏🏽

You can't imagine how motivating you are to all those Algerian students who know you.

Yeah but how do you calculate kolmogorov complexity??

Thanks for the video! Could you please tell me how to calculate the normalized value of the complexity (16:08)?

@Yachine_mahid how could you go about this Make an Artificial Neural Network with dynamic input and binary out .. Using C++ or Java

Please build MultiLayer Perceptron algorithm from scratch with breast cancer dataset

I hope there must be a book that talk about how to convert the math formula into coding

can you introduce the book of how to convert the math into coding?

Quite the video. You explain things quite well. Although I would like to know how to use this for other things other than the xor example. I enjoyed the background music. How would I use this to predict value changes for game item prices. I have a list of the prices and days, would I use say 60 input layers for 60 different price/day values. How many hidden layers would I need? I'm assuming the output layer would remain 1, and report 0 to 1 on how strong it believed in the future number? Thank you so much for your video. You have earned my sub!