Max Kanter - Alteryx Innovation Labs

Alteryx Internship Projects 2020

2020 has been an unprecedented year and Alteryx’s internship and co-op program is no exception.

Analyticon: An Inspired Event for Data People

Tackling the greatest global and societal problems can only happen when everyone works together, regardless of programming language, business vertical, or degree.

Engineering

Featuretools: One year of automating feature engineering

Happy birthday, Featuretools! One year ago, we open sourced Featuretools, making it available to the entire world.

Engineering

What Is Machine Learning 2.0?

As the demand from businesses to leverage machine learning continues growing at an exponential rate, the current time-intensive process that heavily relies on highly-skilled ML experts won’t suffice.

Research

Machine learning 2.0 - Engineering data driven AI products

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

Leadership

Putting Machine Learning to Work

We started Feature Labs with a straightforward goal: build products that enable any organization to create and deploy machine learning solutions. In 2015 while working in the MIT Computer Science and Artificial Intelligence Lab, my co-founders and I developed an automated data science system that outperformed 615 of 906 top

Engineering

Deep Feature Synthesis: How Automated Feature Engineering Works

The artificial intelligence market is fueled by the potential to use data to change the world. While many organizations have already successfully adapted to this paradigm, applying machine learning to new problems is still challenging. The single biggest technical hurdle that machine learning algorithms must overcome is their need for

Leadership

Feature Engineering: Secret to data science success

Feature engineering is challenging because it depends on leveraging human intuition to interpret implicit signals in datasets that machine learning algorithms use. Consequently, feature engineering is often the determining factor in whether a data science project is successful or not.

Use Cases

Applying Data Science Automation to Better Predict Credit Card Fraud

An industry report from 2015 found that one out of every six legitimate cardholders experienced at least one declined transaction because of inaccurate fraud detection in the past year.

Engineering

Bringing data science automation to the domain expert’s playground

In July, we visited Carnegie Mellon University to participate in the 17th annual Simon Initiative’s LearnLab Summer School on Educational Data Mining. During the program, we gave a talk on feature engineering and helped teams complete projects using Featuretools, an open source library for automated feature engineering. Introducing and

Engineering

Open Sourcing Featuretools

I created Deep Feature Synthesis two years ago while I was a student at MIT. My intention from the very beginning was to one day share that technology with the world. That day has finally come, and Featuretools is now available for anyone to use for free. Open-sourcing Featuretools will

Research

Deep Feature Synthesis

Towards automating data science endeavors

Leadership

Introducing our Blog

Feature Labs has come a long way since we started the company in 2015. We’ve spent countless hours developing our technology, working with customers, and traveling the world to share the exciting work we’re doing. Now that Feature Labs is growing faster than ever before, we are launching

Research

Label, Segment, Featurize

a cross domain framework for prediction engineering

Research

Towards increasing data scientists’ productivity by 1000x

How to make data scientists more efficient