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เข้าร่วมเมื่อ 13 ส.ค. 2018
No fancy edits, just content on Machine Learning, Tech, India, World, and some random Gyaan.
Neural net in PyTorch - Backprop (code)
This video contains the implementation part of the backpropagation algorithm in PyTorch. We will be coding the derivatives and then running the full-fledged neural network on the MNIST dataset to calculate the accuracy.
Please do watch the previous derivation video, to make sense of what we are actually coding over here.
Hope you all like it. 😁😁
#education #pytorch #computerscience #machinelearning #coding #programming #maths #python
Please do watch the previous derivation video, to make sense of what we are actually coding over here.
Hope you all like it. 😁😁
#education #pytorch #computerscience #machinelearning #coding #programming #maths #python
มุมมอง: 40
วีดีโอ
Neural net in PyTorch - Backprop (Theory)
มุมมอง 3412 ชั่วโมงที่ผ่านมา
This video includes an depth explanation of the backpropagation algorithm and its working. Here we compute all the derivatives of the loss used in backprop, from scratch. Computing the derivatives from scratch helps to understand how the machine learning model actually learns by minimizing the loss. This video includes the under-the-hood working of PyTorch neural net layers. Hope you all enjoy ...
Neural nets from scratch in PyTorch - Part 1 (Forward prop)
มุมมอง 193วันที่ผ่านมา
This video contains an implementation of a simple fully connected neural net (FCNN) from scratch in PyTorch without the use of any in-built functions. This part contains the implementation of the first half of neural networks ie. forward propagation and loss calculation. Feedback is much welcome. Hope you all like it. 😁
Activation Functions - Basics
มุมมอง 1594 หลายเดือนก่อน
This video summarises the whats and whys of the activation function. Activation functions form one of the pillars of the Deep Learning framework. Going over this video will help you understand one of the fundamentals of deep learning. Hope you enjoy the content. Do let me know your feedback in the comment section.
In's and Out's of attention
มุมมอง 3035 หลายเดือนก่อน
This video covers Attention models more intuitively and practically including minute details that are either left out or forgotten. Attention forms the core of transformers which are currently everywhere. I have tried to cover the heart of transformers both mathematically, and conceptually. Let me know if the code and the slides are required in the comment sections. Feedback is always welcome. 😁😁
It would be helpful if you mention the prerequisite and target audience for these videos in the description. or if you even mention it in the start of the video.
Rodriguez Jennifer Davis Patricia Robinson Mary
Insightful 🤯
Well-explained!
intriguing :)
Good work....keep making such videos .💯💯
Thanks a ton for breaking down transformer implementation!!
Amazing video..I've watched several videos on activation functions before, but yours is by far the most understandable.
perfect explaintion
Thanks ❤
Nice explanation ❤
Good work....keep making videos..❤❤❤❤
I will try my best
Wow, this is incredibly captivating!
Thenks
All the best👍
Thanks
Keep Growing✨ All the best.
Thanks a lot 😊