Thoughts on Deep Learning Tools
I did my first web site at the end of 2001
I remember putting together scripts in Notepad.exe. php, html, tables and styles were are all mixed in the same file, and of course, I would copy and paste the same code in every page. It’s messy but I didn’t know any other alternatives.
Around 2006, Ruby on Rails came in, offering a much more sane way of organizing your project. Model files reflect your real-life objects and sync auto-magically to the database, Controllers take care of user requests, and you put html in Views.
Currently machine learning work is very similar to making websites in 2001. After a dozen iterations, you end up with a *big* python file, mixing up data initialization, layers setup, hyperparameters research, inference etc. Hopefully, we have high-level librairies like Keras. But try to present your work to a third-party, and I will guarantee they will end up confused. A bit like telling everyone that your whole website is in a giant php file.
The way I see it, we could benefit from a framework similar for deep learning, with:
* a data ingestion section would take care of data preparation, data clean-up, and prepare everything for training. Ideally, there would be a nice user interface so that people can go through the data, add new data, correct labels, do a search and select/deselect small or big chunks of data for training
* model files would describe your deep learning layers, such as which activation function is used, size of your convolution, batch size, etc.
* another part of the framework would save automatically trained models, and would also offer a nice interface for inference, prediction or generation, perhaps even a ready-to-use API that can be consumed by a third-party site
* a final part of the system would record all the experiments, hyper-parameters, accuracy, loss and so on
All of this would be more sane. You would be able to share the project on github and get others to participate easily.
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