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 Asia Pacific & Japan

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Dive deeper, develop an effective strategy, and start leveraging the full power of machine learning technologies.

  • Accelerate AI/ML journey
  • Unlocking the benefits of data maturity across Asia Pacific

    Data can be an invaluable source of growth for organizations across Asia Pacific and Japan (APJ). The key to harnessing its true value is analyzing it effectively and creating a data-driven culture. But while the task of maximizing the value of data can come with challenges, organizations can take small steps to unlock its value.

    Half of organizations in APJ have intermediate to master levels of data maturity and are realizing impressive financial rewards. What does this mean and what can organizations do next to improve their data maturity? From building a culture of analytics, to transforming analytics into actionable insights, there are simple steps businesses can take to becoming a data-driven organisation.

    Download the report and get the latest insights from an APJ and country perspective today.

    6 steps to machine learning success

    Businesses can unlock significant value across the organization with the help of artificial intelligence (AI) and machine learning (ML).

    Follow the proven path to machine learning success. The 6 Steps to Machine Learning Success eBook will guide you on your ML journey and help you achieve measurable results at every stage along the way. Read the eBook to learn about:

    • A successful machine learning journey in 6 steps
    • How to transform ML investments into competitive advantages
    • Inspiring stories of industry leaders who’ve successfully implemented machine learning
    • Insights from AWS machine learning experts

    7 leading machine learning use cases

    Move beyond the hype and discover the tangible benefits of machine learning. In this eBook, we have outlined seven leading use cases where businesses have successfully applied machine learning to achieve fast, efficient, measurable results.
    Read the 7 Leading Machine Learning Use Cases eBook to learn more about these use cases and the requirements you should look for when identifying a suitable application for machine learning, such as:

    • Solves real business problems
    • Leverages sources of untapped data
    • Can be completed in a matter of months

    Achieving transformative business results with machine learning

    By providing the broadest and most complete set of machine learning (ML) services, AWS is able to meet its customers wherever they’re at in their ML journeys and help them achieve specific objectives.

    Read the Achieving Transformative Business Results with Machine Learning eBook to learn why hundreds of thousands of organizations use AWS ML to:

    • Improve customer experiences
    • Optimize business operations
    • Accelerate innovation

    Accelerating machine learning innovation through security

    To build successful machine learning models, you often need datasets unique to your business. These datasets are extremely valuable assets and need to be secured throughout every step of machine learning—including data preparation, training, validation, and inference.

    Amazon SageMaker, a fully managed machine learning service, provides comprehensive security features that can help your organization:

    • Meet the strict security requirements of machine learning workloads
    • Secure datasets through every step of the process
    • Go from idea to production faster, more securely, and with a higher rate of success

    Read the Accelerate Machine Learning Through Security eBook to learn how security features from Amazon SageMaker and the AWS Cloud can help you go from idea to production faster.

    Machine learning at scale

    Machine learning (ML) has become a core technology ingredient for organizations to drive real-world innovation, yet many are struggling to bring more ML models into production in a repeatable and responsible way. Read our eBook, Machine Learning at Scale: High-Performance, Low-Cost Machine Learning for Any Use Case, to learn how you can:

    • Democratize machine learning by empowering more users to generate predictions
    • Leverage AWS customer stories to inspire ML success
    • Use MLOps practices to bring models from idea to production
    • Process all types of data at scale to make more accurate predictions

    Democratized, operationalized, responsible: The 3 keys to successful AI and ML outcomes

    A growing number of companies, from emerging startups to established enterprises, are deploying artificial intelligence (AI) and machine learning (ML) to boost innovation and competitive advantage. So, while AI and ML investments are predicted to top $200 billion by 2025, companies want assurances that their initiatives will bear fruit. This eBook details how democratization, operationalization, and responsibility—the three keys to effective adoption—promote successful outcomes.

  • AI use cases
  • IDC MarketScape: AI Life-Cycle Software Tools and Platforms 2022 Vendor Assessment

    The IDC MarketScape evaluated eight vendors and named AWS as a Leader for AI lifecycle software APEJ (Asia Pacific excluding Japan). This report details the capabilities and strategies of vendors that offer solutions across AI model build (and training) software, machine learning operations (MLOps) software, and trustworthy AI software.

    Read the report excerpt to:

    • Gain insights into the AI life-cycle software landscape across APEJ including emerging trends, adoption patterns, and new uses case in demand
    • Understand why the IDC MarketScape named AWS a leader
    • Understand what factors and vendors Data scientists and ML developers consider to identify potential solutions for ML Model development, deployment, Ops and trustworthy AI model management

    Set your document free

    Escape from manual document processing and find freedom in a machine learning solution. Work more efficiently with intelligent document processing.

    Read the Set Your Document Data Free eBook to learn how you can use machine learning to:

    • Enable faster document processing to accomplish what once took months or weeks in a matter of days
    • Improve customer satisfaction by providing your clients with more accurate information faster and with higher efficiency
    • Boost productivity by helping workers spend more time on business-critical tasks

    Accelerate business growth with machine learning

    Machine learning (ML) has become a core component of operations within growth-minded companies, unlocking new opportunities and resolving key challenges.
    Read the Accelerate Business Growth with Machine Learning eBook and learn how you can leverage easy-to-use ML solutions to:

    • Improve the customer experience with faster insights and personalized recommendations
    • Optimize business operations to boost productivity
    • Accelerate innovation with automation

    Improve customer experience by adding AI to your contact center

    It’s time to leave behind the challenges of legacy contact centers—long wait times, misdirected calls, and resolution delays. Instead, deploy the power of machine learning and give customers the solutions they need.
    Read the Improving Customer Experience by Adding AI to Your Contact Center eBook to learn how you can leverage AWS AI services to:

    • Empower customers with self-service technologies
    • Increase agent productivity by providing AI assistance during live calls
    • Identify business improvement opportunities by deriving actionable insights from conversation data
    • Establish efficient call centers and create great customer experiences

    Organizations are hungry to use data to grow and improve performance, but enterprises are struggling with search today. Knowledge is key to business insights, and there are hard costs and risks associated with time spent searching for information or faulty decisions made based on inaccurate information.

    Intelligent search powered by machine learning can help solve these challenges by leveraging natural language understanding and deep learning. Read the Why Your Business Needs Machine Learning-Powered Search eBook to identify areas for organizational transformation, including:

    • Increase employee productivity
    • Improve customer self-service and satisfaction
    • Accelerate research and development

    Drive business growth with personalization

    Personalizing content for online consumers is key to breaking through the noise. Yet brands face challenges that prevent them from providing these seamless, relevant experiences. The result is fractured communications and limited visibility into customer needs.
    Machine learning enables you to provide customers with relevant recommendations and ultimately improve brand loyalty. Read the Drive Business Growth with Personalization eBook to learn:

    • How machine learning can overcome traditional personalization challenges to increase engagement and conversion
    • How industries like Media and Entertainment (M&E) and Retail are leveraging personalization powered by machine learning
    • How a company successfully used machine learning powered personalization to double its response rates for content recommendations
  • Machine learning infrastructure
  • Accelerate machine learning innovation with the right cloud services and infrastructure

    Machine learning has entered the mainstream, powering a wide range of business benefits—such as more accurate business forecasting, personalized customer experiences, and greater operational efficiency.

    Read Accelerate machine learning innovation with the right cloud services and infrastructure and discover how purpose-built services and powerful infrastructure from AWS can help you accelerate every step of the machine learning lifecycle. Learn how you can:

    • Prepare data for machine learning quickly and easily
    • Build accurate machine learning models across multiple frameworks
    • Train machine learning models faster
    • Deploy machine learning models at the lowest possible cost

    Download the eBook now—and discover how you can build a solid foundation for machine learning success at your organization.

    Jumpstart innovation with machine learning

    Machine learning (ML) is transforming industries, with real-world use cases like:

    • Conversational AI
    • Document processing
    • Computer vision
    • Personalized recommendations

    This is all made possible thanks to the cloud. With the cloud’s almost limitless storage, scalable networking, and cost-effective pay-as-you-go model, organizations don’t need to invest in all possible options upfront.

    The benefits of ML are available to everyone.

    Accelerate machine learning development to build intelligent apps faster

    AWS and NVIDIA are helping data scientists and developers to deploy machine learning models more quickly and easily. Read the IDC whitepaper to see how AWS and NVIDIA can help your organization bring intelligent applications to market faster with:

    • Ready-to-use AI services for images, speech, text, and more
    • Amazon SageMaker, a fully managed service to prepare data and build, train, and deploy ML models at scale
    • Open-source frameworks and infrastructure resources for developing, implementing, and scaling ML models for business needs

    Q&A: Choosing the right computer infrastructure for machine learning

    Now that machine learning is within reach for organizations big and small, many executives are asking, “What factors should I consider when choosing machine learning infrastructure and services?” For the answers, we turned to Dr. Bratin Saha, VP of AI/ML services at Amazon. Access the Q&A for a closer look at:

    • How to overcome the key challenges facing developers and organizations
    • Guidance and best practices for evaluating the infrastructure requirements of ML workloads
    • Amazon EC2 compute instances for ML model training and inference

    Propel 4 common machine learning use cases into production

    Making the right infrastructure decisions is essential to getting your ML models into production at scale and at optimal cost. But how can you really ensure that you have adequate infrastructure to support the compute, network, and storage needs of common ML use cases? Read Propel 4 Common Machine Learning Use Cases into Production for practical insights for setting-up your infrastructure for computer vision, fraud detection, natural language processing, and recommendations.
    • Learn about successful results from AWS customers after deploying ML applications
    • Get real-world guidance on evaluating your infrastructure and exploring AWS ML infrastructure solutions
    • Discover practical solutions to the common challenges you may face as your team moves from model concept to production

Featured customers

Learn how these organizations are accelerating business outcomes with artificial intelligence and machine learning.

Learn more about AI & machine learning on AWS

AWS named a Leader in IDC MarketScape for AI lifecycle software tools and platform APEJ 

AWS named a Leader in Gartner Magic Quadrant for Cloud AI Developer Services

100,000+ customers use AWS for machine learning


customers use AWS for machine learning

10x increase in team productivity using Amazon SageMaker


increase in team productivity using Amazon SageMaker

40% reduction in data labeling costs using Amazon SageMaker


reduction in data labeling costs using Amazon SageMaker

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