Tensors for Neural Networks, Clearly Explained!!!

triple bam,!!!!!!!!!!

The simple explanation is that a tensor is something that transforms like a tensor

😃

You are the best teacher on my list !!

BAM, BAM, BAM, BAM..................BAM.. Great Sir

perhaps a top 3 jingle, I really enjoyed it. Even with time to reflect, I am going with: 1) Statquest, its bad to the bone; and 2) were going to do a lot of maths step by step by step... statquest ...the bangers

I am in a bit of a quandary- trying to decide, of your skills, which is superior: you skill as a singer or your skill as a teacher of Machine Learning!

You are amazing bro ! Thanks for the amazing vidoes.

My only question is: Why can tensors run in gpus? I've been trying to find information on it for the longest time and still found nothing.
Why can't numpy arrays be stored in GPU?

Thanks in advance!

PS: Thanks to statquest, I was able to pass my data science class!!

Thank you, i was about to leave this planet because of the wonderful people who are given the task to teach students about ML but cant teach a thing and give zero when they fail eventually.

Basically tensors are arrays:

Zero dimensional array: scalar
One dimensional array: array
2 dimensional array: matrix
n dimensional array: tensor

It’s just been renamed for no good reason. 🤦‍♂️

goood

Interesting. Thanks. I come from manifold/engineering point of view. Which turns out to be a useful mental tool for some sorts of chemistry. Y' have to imagine, often, how some sorts of molecules interact. Using or having a background in manifold or Linear Algebra, turns out an excellent adjunct. Who knew? I thought that the maths were just a lot of fun at the time.

once again, saved my ass

Very interesting way to teach :)

"Tensor cores are processing units that accelerate the process of matrix multiplication", so then we're calling them Tensors instead of Matricies, so we can use Tensor cores, which multiply matricies. Makes sense.

cringy as hell

Subbed. I need more StatQuest in my life.

I thought that I understood ANN, but now I feel that everything is so much more intuitive. Thank you!

Shameless self promotion... :) :) ..

Thank you for this really good explanation!

I think that would be awesome for GRU units and we can compare with LSTM. Please !!!

Triple Ugh

ugh!!!

So Tensors are basically just faster matrices?

And also, is there a difference between tensors and safetensors when talking about image generation AI?

Sir, you have taught me more in few videos than my Professors did in 1 full year. I am ever grateful to you.

Also, could you please do more videos on Tensor flow (theory part e.g., eager/graph execution, name scopes, placeholders etc.)?

Little slow, but great explanation.
Thanks!

Your jokes aren't funny and getting annoying.
Just don't say ugh and bam, it's that simple...

"Mathematicians and machine learning people define tensors in different ways".
This one sentence made a world of difference for my learning.
May be it's just me; but I can't thank you enough.

😆let's go ,I think I can't able to sleep well tonight ,i need at least 3 day to proper classification n get command on it , but as always it's really help me a lot to clear my all the doubts n confusion 💥 💥 double bam 😄 👍

I have a cs study project aboug GNNs and was looking up Tensors. And i was hit by the agony of Tensors in the Context of deep mathematics and physics. The moment i open a CS Video about Tensors im met with music and good vibes <3

BAMM!!!

Simple and nice Tutorial Professor. But,
Expected an In-depth and more ComprehensiveTutorial about Tensor.
Thank you Professor.

looking forward to more fancy topics in Deep Learning. Btw, thanks for sharing.

I liked the intro.
Tensormaster!

I live for the guitar intro and BAMs

As a physicist, now I'm very confused

Loved it. Great vid. An ML explainer I can actually understand. Exciting, such BAM! Gonna watch everything else next. I should take your ML course, I assume you have one -- with exercises and such?

I am in love with tensors after seeing your video🤣

You rock! I learned much more from your series in NN in 3 days than sitting in a machine learning class for one semester!

Another banger

Could you do a video about "Bach training", or what it is called :), and how all partial derivatives are handeld in those situations? For example if they are added into a sum, or that the average derivative is calculated.

Subscribed just for that intro

RNN, NLP and word embedding pliss !!! Tkss!!!

StatSquatch is totally awesome!

I almost quit understanding cnn with the fancy jargons all over the internet. After watching your playlist, you gave me ray of hope. You are freaking genius of explaining things in simplicity. hope to see your playlist with advance cnn topics (object detection, semantic segmentation and siamese network). Thank You 3000

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Bamm !!!

Finally I am not confused as I did not know ML tensor is different from the tensor in maths (even though I still don't know how GPU works)! Thank you!!!