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Resources #948

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H1drogen Jun 3, 2024
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Update 03_pytorch_computer_vision.ipynb
H1drogen Jun 3, 2024
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course initiation
H1drogen Oct 3, 2024
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1 change: 1 addition & 0 deletions 00_pytorch_fundamentals.ipynb
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"You can create your own matrix multiplication visuals like this at http://matrixmultiplication.xyz/.\n",
"\n",
"> **Note:** A matrix multiplication like this is also referred to as the [**dot product**](https://www.mathsisfun.com/algebra/vectors-dot-product.html) of two matrices.\n",
"> Refer to this excellent course to learn more about matrix multiplication https://www.khanacademy.org/math/linear-algebra\n",
"\n"
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1 change: 1 addition & 0 deletions 03_pytorch_computer_vision.ipynb
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"\n",
"## Extra-curriculum\n",
"* **Watch:** [MIT's Introduction to Deep Computer Vision](https://www.youtube.com/watch?v=iaSUYvmCekI&list=PLtBw6njQRU-rwp5__7C0oIVt26ZgjG9NI&index=3) lecture. This will give you a great intuition behind convolutional neural networks.\n",
"* Complete https://www.kaggle.com/learn/intro-to-machine-learning\n",
"* Spend 10-minutes clicking thorugh the different options of the [PyTorch vision library](https://pytorch.org/vision/stable/index.html), what different modules are available?\n",
"* Lookup \"most common convolutional neural networks\", what architectures do you find? Are any of them contained within the [`torchvision.models`](https://pytorch.org/vision/stable/models.html) library? What do you think you could do with these?\n",
"* For a large number of pretrained PyTorch computer vision models as well as many different extensions to PyTorch's computer vision functionalities check out the [PyTorch Image Models library `timm`](https://github.com/rwightman/pytorch-image-models/) (Torch Image Models) by Ross Wightman."
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