Taylor & Letham (2018) Forecasting at Scale
This is the paper for Facebook Prophet.
It considers time series \(y(t)\) as a composition of trend, seasonality, and
holidays under generalized additive model (GAM):
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Glorot & Bengio (2010) Understanding the difficulty of training deep feedforward neural networks
This is the paper that explains what caused the gradient vanishing or exploding
problem in training neural networks. The approach was to experiment with some
fabricated image datasets as well as ImageNet datasets for multi-class
classifications. Then some theoretical derivation is provided to support the
argument.
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Thinking with type
Ellen Lupton / 2010
A nice book for leisure reading, and helps making better decisions on choice of
fonts and page layout. It has a website too: http://thinkingwithtype.com
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van der Maaten & Hinton (2008) Visualizing data using t-SNE
t-SNE is often used as a better alternative than PCA in terms of visualization.
This paper is the one that proposed it. It is an extension to SNE (stochastic
neighbor embedding), which the first few page of the paper outlined it:
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Excel conventions
Excel is quite ubiquitous but not many people use it well. The finance industry use it a lot and there are some good practices created. The key to use Excel (or other spreadsheet) well is to remember that there are two layers in it, the formula and the result, and...
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