How Things Will Proceed
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- What differentiates this blog for my readers?
- What is the best way, for me, of developing my knowledge and master of these techniques?
- What pathway is also going to work for people who are either reading casually, or interested in working through problems at a similar pace?
- Preparing examples and potential future blog posts...
- The MNIST databast. It's included in this code repository which we will also be referring to later when looking at deep learning / neural networks: https://github.com/mnielsen/neural-networks-and-deep-learning
- The Kaggle "National Data Science Bowl" dataset: http://www.kaggle.com/c/datasciencebowl
- The Kaggle "Diabetic Retinopathy" dataset: http://www.kaggle.com/c/diabetic-retinopathy-detection
- Maybe also try a custom image-based data set of your own choosing. It's important to pick something which isn't already covered by existing tutorials, so that you are effectively forced into the process of experimentation with alternative techniques, but which can be considered a categorisation problem so that similar approaches should be effective. You don't need to do this, but it's a fun idea. You could use an export of your photo album, the results of google image searches or another dataset you create yourself. Put each class of images into its own subdirectory on disk.