Experimenting with RNN!
This notebook aims to provide some basic intuition on the differences between two types of deep neural networks and to encourage you to test different deep learning architectures....
Blog
Questions, experiments, and things I wrote down.
Newer pieces follow questions through public data. Earlier posts capture experiments with Python, browser automation, and neural networks. Both live here, with the older posts kept at their original dates and URLs.
Data explorations
Questions I followed through public data.
Housing and market questions, what appeared in the data, and where the evidence stops.
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How did final prices compare with asking prices?
A Stockholm sales snapshot of asking-to-final differences, followed by comparisons between sales with similar recorded characteristics.
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How often was the final marked bid step unusually large?
A comparison of the final marked step with the other positive steps in each eligible auction trace.
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How did later stock-price outcomes differ by holdings direction?
Outcome distributions following public Swedish insider disclosures, compared across holdings directions and four broad recorded-position categories.
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Can weekly observations answer a daily dividend-date question?
Why weekly observations and exact-date matching cannot yet support a daily price-effect conclusion.
Earlier posts
Experiments from 2018.
Python, Selenium, and neural-network notes, preserved with their original publication dates and links.
Play with Selenium Part 2
Second part is to clean the code and make it easy to work with.
Play with Selenium Part 1
First part, a fast walk through of selenium with a goal to click on a object.
Python Decorators
I'll walk through some example where decorator can is been used.