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Top 7 machine learning use cases for startups

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Market pressures, like the transition to remote work and the need for greater online collaboration, are disrupting workflows and challenging today's startups to do more with less—and continue to grow in the face of uncertainty. Emerging technologies help startups maintain control, bringing their people together to respond to modern challenges with innovation and data-driven intelligence. With its ability to intelligently predict outcomes and produce more accurate results over time, machine learning is helping startups realize the exact advantage they need. Startups across nearly every industry are leveraging machine learning to reduce costs, boost productivity, create better products, and get to market faster than their competitors. AWS provides machine learning services for every use case—so startups of any size can launch immediately. AWS is among the top rated on Stanford's Solve business challenges with machine learning 2020 deep learning benchmark, DAWNBench, for the fastest training time, lowest cost, lowest inference latency, and deepest set of security features. 1 Startups also choose AWS for its proven experience and reliability. More machine learning happens on AWS than anywhere else, and AWS is the home of 89% of deep learning projects in the cloud. And AWS allows startups to experiment with and customize machine learning algorithms using popular frameworks—91% of PyTorch and 92% of TensorFlow projects in the cloud happen on AWS. 2 Machine learning can give your organization the advantage it needs to capitalize on big opportunities and thrive in today's challenging startup environment. With AWS machine learning, you can spend less time on manual, repetitive tasks and guesswork—and more time creating irresistible customer experiences that set your organization apart. 1 2 2 INTRODUCTION

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