MrinmoiHossain/Udacity-Deep-Learning-Nanodegree
The course is contained knowledge that are useful to work on deep learning as an engineer. Simple neural networks & training, CNN, Autoencoders and feature extraction, Transfer learning, RNN, LSTM, NLP, Data augmentation, GANs, Hyperparameter tuning, Model deployment and serving are included in the course.
This resource provides comprehensive learning materials for anyone aspiring to become a deep learning engineer. It takes you from understanding basic neural networks to implementing advanced techniques like convolutional networks for image recognition and recurrent networks for sequence generation. The output is a strong foundation in deep learning theory and practical skills in PyTorch for building and deploying AI models.
No commits in the last 6 months.
Use this if you are an aspiring AI engineer or data scientist looking to gain expertise in deep learning, particularly with the PyTorch framework.
Not ideal if you are a non-technical user looking for an out-of-the-box solution to a specific deep learning problem without learning the underlying principles.
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GPL-3.0
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Last pushed
Aug 23, 2022
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