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  • The Intuitions Behind Bayesian Optimization with Gaussian Processes

    by Charles Brecque on KDnuggets
    In certain applications the objective function is expensive or difficult to evaluate. In these situations, a general approach consists in creating a simpler surrogate model of the objective function which is cheaper to evaluate and will be used instead to solve the optimization problem. Moreover, due to the high cost of evaluating the objective function, an iterative approach is often recommended. Iterative optimizers work by iteratively requesting […]
  • Hi Renzo,
    by Charles Brecque on 16/01/2019 at 14:36

    Hi Renzo,Thank you for your question. There are no limitations on the amount of data you supply so you can also add six months of evolution of the same account.Best,Charles […]

  • Thank you Radhika! Please don’t hesitate if you’d like to try OPTaaS for your research.
    by Charles Brecque on 09/01/2019 at 08:25

    Thank you Radhika! Please don’t hesitate if you’d like to try OPTaaS for your research.Best wishes,Charles […]

  • Congratulations to Osler! A massive achievement for the Oxford spin-out ecosystem.
    by Charles Brecque on 08/01/2019 at 14:44

    Congratulations to Osler! A massive achievement for the Oxford spin-out ecosystem. […]

  • Bayesian Optimization & Quantum Computing
    by Charles Brecque on 08/01/2019 at 14:09

    (source)How Bayesian Optimization can help Quantum Computing become a realityQuantum computers have the potential to be exponentially faster than traditional computers which will revolutionise the way we currently solve a number of applications. You can find out how in this detailed article but we are still years away from general purpose Quantum Computers. However, for certain applications Bayesian Optimization can help stabilise quantum circuits and this article will summarise how OPTaaS […]

  • Forecasting variable Travel expenses with 95% accuracy
    by Charles Brecque on 18/12/2018 at 16:05

    (source)Automated Machine Learning for CFOsMillions of dollars are spent each year by organisations on travel expenses of which are large proportion is variable and difficult to estimate. Apart from the Air Fare and the Accommodation which are known at the time of the booking, additional expenses such as meals and incidentals are unknown and can have a big impact on the total expenses.In this article we are going to build a model in minutes that can work out the variable expenses based on […]

  • Clustering Fifa Players
    by Charles Brecque on 14/12/2018 at 13:40

    (source)Are all football players the same?There are 11 positions in a football team who play in various roles, the 4 main ones being:Goal keepersDefendersMidfieldersStrikersWith this impressive data set including stats for every single FIFA 18 player, scraped from Sofifa we are going to see if AuDaS, an Automated Data Science platform developed by Mind Foundry, can automatically detect these classes and whether we can extract any insights.Preparing the dataThe data covers 17,000 […]

  • Optimize your Email Marketing strategy with automated Machine Learning
    by Charles Brecque on 10/12/2018 at 21:58

    (source)Optimizing Marketing spend for Sales is a billion dollar question for businesses across the world as over $1 trillion annually has been dedicated to the task since 2017. However, understanding the relationship between marketing budgets, actions and associated sales is challenging due to the many simultaneous and competing internal and external factors which influence sales (psychology, weather, mood, location, price, ads …).Machine Learning techniques have shown promising […]

  • Credit Card Clustering
    by Charles Brecque on 10/12/2018 at 21:55

    (source)Automated Clustering with AuDaSThe number one challenge faced by marketers is to understand who they are selling to. When you know your buyers’ personas you can tailor your targeting and offerings to increase their satisfaction and your revenue as a result. When you already have a pool of customers and enough data on them, it can be very useful to segment them. In this article, we are going to see how we can use clustering to segment some credit card customers. The data for […]