Alteryx’s recent acquisition of Feature Labs, a startup focused on feature engineering for machine learning and AI, is but the latest example of how acquisitions are driving innovation and competition in the data and analytics space.
This technology-driven acquisition will complement Alteryx's recently unveiled assisted modeling capability that guides users through the process of building ML models.
What is feature engineering and why is it important
According to AI expert Dr. Jason Brownlee, feature engineering is
The process of transforming raw data into features that better represent the underlying problem to the predictive models, resulting in improved model accuracy on unseen data.
This is a fundamental and foundational part of building a machine learning model; surveys of AI and ML experts suggest it is the most important factor determining the successful outcome of a model.
Max Kanter, CEO and cofounder of Feature Labs, wrote that the company plans to use this acquisition to help “business analysts that desire code-free tools that can guide them through the complex process to successfully implement AI and ML techniques with their domain knowledge.”
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