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Bayesian Optimization as a Service for Quantitative strategies

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 Charles Brecque, Operationalising Machine Learning via automated web-services

 Tuesday, May 29, 2018

Our Oxford University Machine Learning spin-out, Mind Foundry, has just released a general purpose Bayesian Optimizer deployed via web-services (OPTaaS). It can optimize any trading models/strategies/pipelines without accessing the models or the data and handles any type of parameters. You can start playing with OPTaaS in this public Jupyter notebook tutorial (https://tutorial.optaas.mindfoundry.ai ) and find out more here: https://www.slideshare.net/CharlesBrecque/optaas-v2 Don't hesitate to contact me for API keys: optaas@mindfoundry.ai


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5 comments on article "Bayesian Optimization as a Service for Quantitative strategies"

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 Charles Brecque, Operationalising Machine Learning via automated web-services

 Tuesday, May 29, 2018



Read more about the OPTaaS API here https://public.optaas.mindfoundry.ai/


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 Scott Boulette, Algorithmic Trading

 Tuesday, May 29, 2018



Very interesting concept


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 Charles Brecque, Operationalising Machine Learning via automated web-services

 Wednesday, May 30, 2018



Feel free to contact me for a trial, I would appreciate your feedback!


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 Gary Boetticher, Associate Professor at University of Houston Clear Lake

 Thursday, May 31, 2018



How does this differ from the optimization feature in AmiBroker?


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 Charles Brecque, Operationalising Machine Learning via automated web-services

 Friday, June 1, 2018



Hi Gary, optimization in AmiBroker doesn't scale easily beyond 2 parameters. It also doesn't allow you to optimize a modular trading pipeline (model selection, training window, forecasting horizon, portfolio selection rule) but only modules of the pipeline.

OPTaaS is the fastest and most flexible global optimizer on the market.

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