theairbend3r/how-to-train-your-neural-net
Deep learning research implemented on notebooks using PyTorch.
This project offers practical, detailed examples for building and training deep learning models across various tasks. It takes raw data like images, text, or tabular datasets and shows how to process them to train neural networks that can classify, segment, or forecast. It's designed for machine learning engineers and researchers who need to implement or understand different deep learning architectures using PyTorch.
No commits in the last 6 months.
Use this if you are a machine learning practitioner looking for concrete PyTorch implementations of deep learning models for computer vision, natural language processing, or time series forecasting.
Not ideal if you are not a developer and are looking for a no-code solution or a high-level API to integrate into an existing application.
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65
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20
Language
Jupyter Notebook
License
GPL-3.0
Category
Last pushed
Oct 30, 2021
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