How are other ML teams overcoming their challenges?

As more companies leverage ML to drive innovation in their business, many are finding the tools and processes to be disconnected, unreliable, and unscalable

A survey of over 500 U.S. ML practitioners uncovered challenges related to people, processes, and tools that are causing friction during the complex process of developing ML. This friction can cause delays in ML development and halt model deployment to production.

Download our 2021 Machine Learning Practitioner Survey to read the complete report and learn:

  • Four challenges companies face in developing machine learning
  • Why most ML practitioners scrapped 40-80% of their experiments in the past year
  • The biggest pain points slowing down AI roadmaps
  • Three characteristics to consider when evaluating tools to reduce friction and accelerate the ML development process