No longer limited to global technology enterprises and data science specialists, machine learning (ML) has entered the mainstream. Thanks to the cloud, the barriers to widespread use of machine learning are rapidly disappearing. The cloud brings together data, low-cost storage, security, and machine learning services along with high-performance, cost-effective CPU- and GPU-based compute instances, which are essential to machine learning success. The cloud also offers a payas- you-go cost model that further enables customers to control costs.
Most Recent Flipbooks
Download the report and learn how to save 50% of time on text and data content comprehension.
AWS Contact Center Intelligence solutions – Boost efficiency, agent productivity, and customer satisfaction by powering your existing contact centers with artificial intelligence and machine learning.
This ESG Economic Validation focused on the quantitative and qualitative benefits organizations can expect by using the Amazon Kendra Intelligent Search to find information quickly and accurately.
Read this eBook to learn how machine learning can help you incorporate behavioral data to personalize the individual customer’s experience and more.
Read the eBook to learn how you can add AI and ML to your existing contact centers to increase customer satisfaction with more accurate answers, reduce call wait times, and derive actionable insights.
Set Your Document Data Free
Read this eBook and learn how you can use machine learning to process data faster, lower costs with intelligent document processing, and boost employee productivity by freeing time for other tasks.
In this eBook, we highlight 7 ML use cases that startup customers are achieving success with today. These use cases solve real business problems and can be completed quickly, with limited budgets.
Learn how 4 startups are leveraging machine learning to solve key challenges and unlock new opportunities.
Read this eBook to learn how 4 digitally native companies are using machine learning to solve key challenges and sustain competitive advantages.
Democratized, operationalized, and responsible: the 3 keys to successful AI and ML outcomes
This eBook will show you how to to succeed with artificial intelligence and machine learning. Use the three keys for effective adoption to promote successful outcomes.
6 steps to a successful machine learning journey
Read this eBook to learn how to achieve success with machine learning. Follow the 6 steps to achieve measurable results at every stage of your ML journey.
This eBook outlines the 7 leading use cases for machine learning that solve business problems. Read customer quotes detailing how an AI service and/or Amazon SageMaker helped solve for these problems.
This eBook discusses the importance of an end-to-end platform to scale ML initiatives across an organization, addressing the need for data preparation, MLOps, low-code/no-code, and responsible AI.
This HBR briefing paper explores the 3 keys to successfully implementing and scaling AI and ML to unlock the value of data across your business.
This eBook highlights how AI and ML go beyond day-to-day business to transform our society - showcasing how organizations are using ML to help fight climate change, improve human health, and more.
Achieving transformative business results with machine learning
This eBook highlights key customer stories, across industries and use cases, focused on how machine learning on AWS has helped transform business and solve real world problems.
Easily prepare data, and build, train, and deploy machine learning applications with AWS.
Accelerate machine learning with low-cost, high-performance, ML-optimized infrastructure.
