Ressources.md

Collection of Ressources for creating sophisticated trading algorithms (unsorted)

• Deep learning for Ruby, powered by LibTorch: https://github.com/ankane/torch.rb

• Simple, powerful data frames for Ruby: https://github.com/ankane/rover

• Pandas wrapper: https://github.com/mrkn/pandas.rb

• higher-level grammar for visual analysis (Univ. Washington): https://github.com/vega/vega-lite

• candlestick charts in vega: https://vega.github.io/vega-lite/examples/layer_candlestick.html

• Ruby library for visualizing your data in a simple way. https://github.com/red-data-tools/charty

• call matplotlib from Ruby language. This is built on top of pycall: https://github.com/mrkn/matplotlib.rb

• calculate statistical summary in arrays and enumerables: https://github.com/mrkn/enumerable-statistics

• call and partially interoperate with Python from the Ruby language. https://github.com/mrkn/pycall.rb

• call numpy from Ruby language. This uses pycall: https://github.com/mrkn/numpy.rb

• Deep learning for Ruby, powered by LibTorch: https://github.com/ankane/torch.rb