A collection of PyTorch notebooks for studying and practicing deep learning. Each notebook contains a set of exercises that are specifically designed to engage and encourage the learner to conduct more research and experiments. (Work in progress!)
Name | Description | Category | Level | Link | Blog |
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Implementing a Logistic Regression Model from Scratch | Learn how to implement the fundamental building blocks of a neural network using PyTorch. | Machine Learning | Beginner |
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PyTorch Hello World | Create a hello world for deep learning using PyTorch. | Deep Learning | Beginner |
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PyTorch Quickstart | Learn about PyTorch's basic building blocks to build and train a CNN model for image classification. | Image Classification | Intermediate |
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A Gentle Introduction to PyTorch 1.2 | This comprehensive tutorial aims to introduce the fundamentals of PyTorch building blocks for training neural networks. | Neural Networks | Beginner |
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Building RNNs is Fun with PyTorch | This notebook teaches you how to build a recurrent neural network (RNN) with a single layer, consisting of one single neuron. It also teaches how to implement a simple RNN-based model for image classification. | Neural Networks | Beginner |
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A Simple Neural Network from Scratch with PyTorch and Google Colab | In this tutorial we implement a simple neural network from scratch using PyTorch. | Neural Networks | Beginner |
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