Five Reasons to Love Automated Machine Learning

February 14, 2019
· 3 min read

There’s a lot to love when it comes to automated machine learning. At DataRobot, we see firsthand the game-changing results that businesses get from this powerful technology. Check out five key reasons businesses are falling head over heels:

  1. Democratization. Everyone wants to solve problems and find solutions. Keeping customers, improving pricing, moving products faster, and making operations more efficient are just a few of the ways automated machine learning can move AI-driven businesses from problem to solution. But AI can be intimidating to many people. It doesn’t have to be. With the democratization of AI and machine learning, you can engage many more people beyond data scientists in AI projects, getting the results you need without hesitation or fear. Data engineers, data analysts, software engineers – these are the people in your organization who will be smitten with automated machine learning.

  2. Guardrails. One of the things holding people back from engaging in AI is the fear of making mistakes. DataRobot’s automated machine learning solution has built-in best practices from some of the world’s leading data scientists, so you can deliver expert-level results every time. These guardrails make sure you can’t forget a critical step or do something out of the ordinary that could sink the project. Whether it’s preventing target leakage or ensuring proper data partitioning, we’ve got you covered.

  3. Transparency and Interpretability. While people want a solution that protects them from mistakes, they also want to be able to dig deep into the data. Which information has the most influence on the model’s accuracy? How accurate is the model overall based on past predictions? Will more data help us develop a better model and look at the problem more deeply, or are the gains to be had negligible? With DataRobot, all of this is possible. Data scientists get to dig as deeply as they want into the models, and data analysts get to explore their questions from different angles so they can always trust the results. There is no black box, and with DataRobot, you will always feel confident about the results you are presenting.

  4. Data Scientist Productivity. Data scientists are busy. They are tackling more and more projects, a lot of which are tedious and repetitive. With the ability to automatically train data against hundreds of the latest machine learning algorithms, automated machine learning enables them to build models in a fraction of the time it would take to do it manually. They can also automate a lot of repetitive data science tasks by automating the pre-processing, feature engineering, and model validation for each model they create. Automated machine learning allows them to reduce the mundane work so they can focus on more complex and strategic projects. What’s not to love?

  5. AI-Driven Enterprise. Imagine this vision of your organization. You are retaining more customers than ever before. Your pricing is on point. You are making decisions based on the latest data, with insight from machine learning models instead of gut instincts. This is what it means to be an AI-driven enterprise. When AI is used strategically and effectively, you are harnessing the power of your data to drive results in every area of your business.

How about you? How has automated machine learning transformed your business? Share the love below in our comments section.

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About the author
Bob Laurent
Bob Laurent

Sr. Director of Product Marketing at DataRobot

Prior to DataRobot, he ran product marketing at Alteryx, where he was responsible for driving awareness and growing a loyal customer base of empowered data analysts. He has more than 20 years of marketing, media relations, and telecom network engineering experience with Fujitsu and NYNEX (now Verizon). Bob resides in Dallas with his wife and two boys, and holds a Bachelor of Science degree from Clarkson University, plus an MBA from New York University’s Stern School of Business.

Meet Bob Laurent
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