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Lectures
https://nbviewer.org/github/fastai/fastbook/blob/master/09_tabular.ipynb
Learn how to deal with tabular data. Explore techniques beyond deep learning.
https://nbviewer.org/github/fastai/fastbook/blob/master/08_collab.ipynb
Learn about embeddings and dot products.
https://nbviewer.org/github/fastai/fastbook/blob/master/07_sizing_and_tta.ipynb
Learn normalization, progressive resizing, and test time augmentation.
https://nbviewer.org/github/fastai/fastbook/blob/master/06_multicat.ipynb
Learn how to adjust your image classifier for multi-label or regression tasks.
https://nbviewer.org/github/fastai/fastbook/blob/master/05_pet_breeds.ipynb
Learn techiniques to scale and impove accuracy of your image classifier.
https://nbviewer.org/github/fastai/fastbook/blob/master/04_mnist_basics.ipynb
Learn fundamental concepts behind deep learning using a computer vision example.
https://nbviewer.org/github/fastai/fastbook/blob/master/03_ethics.ipynb
Learn why ethics is important and how to apply it in deep learning applications.
https://nbviewer.org/github/fastai/fastbook/blob/master/02_production.ipynb
Computer vision example of building an end-to-end deep learning application.
https://nbviewer.org/github/fastai/fastbook/blob/master/01_intro.ipynb
Book overview. Introduce the key concepts behind deep learning, and train our first models on different tasks.
https://course.fast.ai/Resources/book.html
Deep Learning for Coders with Fastai and PyTorch: AI Applications Without a PhD