Research - Alteryx | Innovation

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Research

Feature Labs was born from our work at MIT. Here's a sampling of our work.

Choosing an API framework for your TypeScript backend

Choosing an API framework for your TypeScript backend

If you’re a backend developer, you’re probably aware of Node.js. If you’re not, it’s a run-time environment that includes everything required to execute a program written in JavaScript. It’s both efficient and scalable, which has made it one of the best ways to develop

Type Inference for Natural Language

Type Inference for Natural Language

One step in natural language data analysis is actually recognizing whether or not our data can be defined as natural language.

Machine learning 2.0 - Engineering data driven AI products

Machine learning 2.0 - Engineering data driven AI products

A paradigm shift from the current practice of creating machine learning models.

Deep Feature Synthesis

Deep Feature Synthesis

Towards automating data science endeavors

Label, Segment, Featurize

Label, Segment, Featurize

a cross domain framework for prediction engineering

What would a data scientist ask?

What would a data scientist ask?

Automatically formulating and solving prediction problems

Towards increasing data scientists’ productivity by 1000x

Towards increasing data scientists’ productivity by 1000x

How to make data scientists more efficient