I stumbled upon Dynamic Notions by John Wakefield where he applies a Backpropogation Neural Network to gain an edge in race track, financial betting. Wakefield has made the entire code sample available in this post along with pretty simple guide lines.
What's really cool here is how he's able to graphically display the data separation, i.e. classification (e.g. up or down predictions) process, which usually runs with mathematical complexity. The user can then visually understand, somewhat, of what the numbers are doing.
What's really cool here is how he's able to graphically display the data separation, i.e. classification (e.g. up or down predictions) process, which usually runs with mathematical complexity. The user can then visually understand, somewhat, of what the numbers are doing.
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