FastAI is a user-friendly deep learning library that simplifies complex machine learning tasks. It provides pre-built models and tools to make it easier for beginners to create powerful AI applications without needing extensive coding knowledge.
Higlights:
In general it is a good library to be used with PyTorch in order to make fast ready to use Deep Learning models. I created a model capable of identify if an image was or was not Pizza. below i will write what were the advantages and disadvantages that i found so far:
Advantages
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Very fast and easy way of create DNNs
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We can select pre trained architectures or train our own
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We have some good built in functions to prepare data and visualize results
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It seems that it is a widely used library and has a good quantity of possible different uses
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Not so bad documentation (not extraordinary either)
Disadvantages
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It looks too short for certain more difficult tasks
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it could have more pre-trained architectures directly implemented
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Do not know if it is that usefull to use if you already master PyTorch or Tensorflow
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Sometimes if you wanna understand what is happening you need to go read the source code
Work done to test this
https://www.kaggle.com/code/franciscomesquita/pizzaornotpizza-pytorch-fastai-97-acc-effnet