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Driverless AI<\/a> is the latest product from H2O.ai<\/a> aimed at lowering the barrier to making data science work in a corporate context. The tool assists non-technical employees with preparing data, calibrating parameters and determining the optimal algorithms for tackling specific business problems with machine learning.<\/p>\n At the research level, machine learning problems are complex and unpredictable \u2014 combining GANs and reinforcement learning in a never before seen use case takes finesse. But the reality is that a lot of corporates today use machine learning for relatively predictable problems \u2014 evaluating default rates with a support vector machine, for example.<\/p>\n But even these relatively straightforward problems are tough for non-technical employees to wrap their heads around. Companies are increasingly working data science into non-traditional sales and HR processes, attempting to train their way to costly innovation.<\/p>\n All of H2O.ai\u2019s products help to make AI more accessible, but Driverless AI takes things a step further by physically automating many of the tough decisions that need to be made when preparing a model. Driverless AI automates feature engineering, the process by which key variables are selected to build a model.<\/p>\n H2O built Driverless AI with popular use cases built-in, but it can\u2019t solve every machine learning problem. Ideally it can find and tune enough standard models to automate at least part of the long tail.<\/p>\n The company alluded to today\u2019s release back in January when it launched Deep Water<\/a>, a platform allowing its customers to take advantage of deep learning and GPUs.<\/p>\n We\u2019re still in the very early days of machine learning automation. Google CEO\u00a0Sundar Pichai generated a lot of buzz at this year\u2019s I\/O conference when he provided details on the company\u2019s efforts to create an AI tool<\/a> that could automatically select the best model and characteristics to solve a machine learning problem with trial, error and a ton of compute.<\/p>\n![\"\"](\"https:\/\/i0.wp.com\/rsoftsolution.com\/blog\/wp-content\/plugins\/RSSPoster_PRO\/cache\/99d88_screen-shot-2017-07-06-at-7-41-12-am.png?resize=640%2C347&ssl=1\")
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