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Dive deeper, develop an effective strategy, and start leveraging the full power of machine learning technologies.
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AWS E-books
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MIT, IDC, IDG reports
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Training & Certification E-books
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AWS E-books
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The machine learning journey
Businesses have the opportunity to unlock significant value across the organization with
the help of machine learning and AI. Follow the proven path to machine learning success. Read the e-book to discover:- The full machine learning journey in 6 steps
- How to transform investments into business-differentiating solutions
- 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 e-book, we have outlined seven leading use cases where businesses have successfully applied machine learning to achieve fast, efficient, measurable results. Read the e-book 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
Machine learning enterprise guide
Enterprises feeling the pressing need to embrace machine learning face challenges unique to their organizations and industries. Successful adoption requires the foresight of executives who understand the scale of implementation and the relevant business objectives—all while strategically avoiding the typical pitfalls that can hinder rapid implementation. AWS created this guide to:
- Help executives tackle the implementation of machine learning in a manageable framework
- Demonstrate the deep insights and business gains achieved when this technology is efficiently deployed and effectively leveraged
- Share examples of enterprise customers that run on AWS tools and technologies and are seeing real business results
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
Tackling our world’s hardest problems with machine learning
With the evolution of machine learning technologies, industries and categories are now using the power of machine learning for the benefit of society. Learn how innovators are tapping into the best practices, in-depth expertise, and powerful solutions of companies like AWS to launch new initiatives and solutions that are improving lives and protecting our planet right now, including:
- Advances in medicine
- Supporting our veterans
- Housing the homeless
- Reducing carbon emissions
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MIT, IDC, IDG reports
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Accelerate machine learning development to build intelligent apps faster
Predict business outcomes, drive value, increase developer productivity, and accelerate innovation in your organization by reconsidering how your business builds intelligent applications. Read the IDC whitepaper from AWS and Nvidia to learn how Amazon SageMaker and deep learning on AWS help solve typical development challenges such as:
- Model development
- Deployment
- Data curation
- Integration
- Management
You’ll gain a deeper understanding of how successful models and products are developed and deployed within modern cloud environments.
A strategic playbook for data, analytics, and machine learning
If your organization is like most others, the pressure is on to use data, analytics, and machine learning to drive critical business decisions, including:
- When to expand product offerings
- How to introduce new revenue streams
- Where to automate manual processes
- How to optimize interactions with customers and business partners
Download the IDG CIO Playbook for help refining your data-driven strategy so you can effectively scale analytics and machine learning across your enterprise. Get the guidance you need to accelerate innovation and drive your business forward with data.
The AI & machine learning imperative
Machine learning is transforming how businesses innovate with AI. Still, many leaders find it difficult to sift through the market hype in search of meaningful value.
This guide can help decision makers at every stage of the journey confront and resolve challenges across the three key levels of AI adoption: leadership, organization, and talent.
What leaders must know about data for machine learning
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
Transform your workforce with skills for machine learning
Upskilling is essential to preparing a workforce for machine learning’s continued march into the mainstream. This guide provides a framework for action on closing the machine learning skills gap by developing capabilities and aptitudes already present in an organizations workforce.Download the guide to discover how to:
- Access and identify gaps in your workforce with skills for machine learning
- Create a framework for getting it done
- Launch and maintain a training program
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Training & Certification E-books
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Training and certification for your machine learning journey
Machine learning, a foundational mechanism enabling artificial intelligence (AI), is one of the most empowering fields within IT today. However, a lack of trained and certified machine learning talent has become a barrier to the widespread adoption of the technology. In this e-book, we’ll review the promise of machine learning and how innovations in training and certification give developers and data scientists an advantage by equipping them with the skills to help their organizations achieve success.
How machine learning skills can advance careers
By improving their machine learning skills, developers and data scientists can accelerate or expand their careers, provide more value to their organizations, and increase their teams’ standing. Much of this can be achieved by transforming the growing IT skills gap—the separation between the capabilities of advanced technologies and the abilities of internal teams to fully capitalize on them—into an opportunity.
Machine learning path: Developer skills tracker
The AWS Training and Certification Machine Learning Path: Developer is a curated curriculum of self-paced digital, virtual classroom, and in-person classroom courses designed for developers, software engineers, and builders who want to become machine learning subject-matter experts. Most courses are free and available on demand—so you can study machine learning and real-world applications however, whenever, and wherever you want.
Machine learning path: Data scientist skills tracker
The AWS Training and Certification Machine Learning Path: Data Scientist is a curated curriculum of self-paced digital, virtual classroom, and in-person classroom courses designed for data scientists—and all those skilled in mathematics, statistics, and analysis—who want to become machine learning subject-matter experts. Most courses are free and available on demand—so you can study machine learning theory and real-world applications however, whenever, and wherever you want.
Learn more about Machine Learning on AWS
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Featured Customers
Learn how these organizations are accelerating business outcomes with artificial intelligence and machine learning.

Elenium enables safer and smoother airport travel using AWS
Benefits: Rapidly deployed a touchless, self-service early-detection health tool to make airport travel safer and 60% more efficient.
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Domino’s Pizza Enterprises delivers in record time using AWS for predictive ordering
Benefits: Delivers pizza in 10 minutes or less through accurate predictive ordering solution.
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Games24x7 uses machine learning on AWS to personalize the gaming user experience
Benefits: Enhances user experience and iterates fast to bring new features to market.
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USG Boral launches an AI safety system on AWS
Benefits: Developed an intelligent warehouse safety system to prevent accidents, able to perform near real-time analytics that processes at least 12 images per second.

Lotte Mart uses Amazon Personalize to increase engagement, purchase rates, and build loyalty.
Benefits: Generates tailored recommendations at scale at 50% of development time.
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ViSenze powers visual shopping experiences with AWS.
Benefits: Built a recommendation engine for visually similar products and product tagging that led to 50% higher click-through and 5x conversion rates.
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Deliveroo uses machine learning on AWS to forecast and predict orders.
Benefits: Developed a system that predicts meal prep time, driver pickup and delivery times to ensure efficient use of drivers.
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Intuit improves customer experience with Amazon Connect, an AI-powered omnichannel contact center.
Benefits: Deploys contact center in 2 weeks instead of 6 months and scales to support 11,000 agents in minutes.
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Urbanbase launches services 20x faster using Amazon SageMaker.
Benefits: Accelerated development 100x faster and service launches 20x faster.
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CoinJar builds world-class cryptocurrency exchange on AWS.
Benefits: 50% cost savings and faster identity verification with Amazon Rekognition.
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Disney uses machine learning to sort through a universe of content
Benefits: Tags content automatically with descriptive metadata to make the archiving process more efficient.
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ZS helps pharma companies navigate change with analytics on AWS
Benefits: Accelerates time-to-market by 20% using Amazon SageMaker and lowers data processing costs by 30%.
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NTT DOCOMO uses AWS to build cell tower inspection tool that cuts costs, improves safety
Benefits: Developed an image recognition system that saves more than 2,000 hours and $100,000 in 2020 with zero cell tower-related accidents.
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Yanolja brings personalized experiences to travelers with AWS
Benefits: Uses Amazon Rekognition to run predictions of guests’ profile and create tailored experiences to drive higher engagement and loyalty.

BGL brings deep learning to super funds with AWS
Benefits: Through Tensorflow on AWS, BGL could apply deep learning to tasks such as compliance categorization and transactional pattern recognition to manage 300 million transactions.
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Biz2Credit improves efficiency of credit application process time by 3-5x using AWS
Benefits: By using AI/ML, Biz2Credit reduced the turnaround time for loan approvals from 7-10 days to 24-48 hours.
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Parcel Platform uses AWS to boost customer lifetime value by 40%
Benefits: Lowered servicing cost per customer while allowing customers to independently track their parcels.
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Formula 1 accelerates cloud transformation with machine learning
Benefits: Using Amazon SageMaker, F1 is training deep learning models with 65 years of historical race data to extract critical performance statistics, make predictions, and give fans insight into the split-second decisions and strategies adopted by race teams.
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