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Exclusive Offer for the TWiML Community

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SigOpt is proud to partner with This Week in Machine Learning and AI as they continue to enable, bolster and provide a platform to the broader modeling community.

As enterprises scale their investment in modelers, models and the model productionalization process, it quickly becomes critical to support and standardize the modeling process with infrastructure. Modeling-driven companies like Facebook, LinkedIn, Airbnb, Stripe and Two Sigma have built internal modeling platforms to address this challenge. Learning from their experience and teasing out the most important components of these platforms will give the broader community a headstart in their journey to become modeling driven.

These companies have rightly identified that supporting model experimentation and optimization with software solutions is essential to building the best models. SigOpt offers enterprise software that standardizes and scales experimentation and optimization for any combination of modeling frameworks, libraries, computing infrastructure and environment. Teams like Two Sigma rely on this solution to realize better modeling results much faster than was previously possible.

Of course, to fully grasp its potential it is best for you to try it yourself. This is why SigOpt is giving an exclusive offer to the TWiML community to try our solution on some of your toughest modeling problems for free. Take advantage of this limited time offer by filling out the form below. 

For those performing research in academia or at nonprofits that you intend to publish, note that you can always take advantage of this kind of offer by signing up for a free version of our product through our academic program. This program is designed to help us give back to the broader community in recognition of how critical their contributions are to where we are today – and will be tomorrow. Learn more about the program here.

Our mission is to accelerate and amplify the impact of modelers everywhere. We hope you find value in our solution and look forward to learning more about how you use it to amplify your research process.

  • How important is it to have the best version of a model?
  • How many models do you have in production today, and/or expect to have in production in 6 months?
  • How many people and/or teams in your org. are working on model development?
  • What kinds of models/libraries are your team(s) working with?
  • On what cadence do you generally develop new, or update existing, production models?
  • On what timescale does your data change?
  • How often do you optimize your models?
  • How do you currently optimize your models?
  • When evaluating new, or comparing new to old, models, how important is it to have a consistent baseline, and confidence in that baseline?
  • Which of these pains are you feeling due to your current optimization method?
  • What kind of evaluation infrastructure do you have?