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.

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.

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
  

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
  

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.

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.

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.

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.