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6 steps to a successful machine learning with Sagemaker

75% of enterprises will start operationalising AI by the end of 2024 and 66% view AI as critical to success.

Artificial intelligence (AI) and machine learning (ML) can increase agility, streamline processes, boost revenue by creating new products and improving existing ones. They also enable faster decision making. Amazon SageMaker simplifies the process of creating models and lowers the barrier to entry, enabling machine learning technologies and initiatives to scale more effectively.

Many organisations are solving scalability problems with Amazon SageMaker, an end-to-end solution that covers the entire ML workflow to prepare data and build, train, and deploy ML models. By using SageMaker, an organisation can get its models into production faster and at a lower cost, enabling the sustainable expansion of ML initiatives beyond pilot projects.

Follow the proven path to machine learning success:

  • The full machine learning journey in 6 steps
  • How to transform investments into organisationally differentiating solutions
  • Inspiring stories of industry leaders who have successfully implemented machine learning
  • Insights from AWS machine learning experts

Think of it as an instruction manual to guide you on your journey at every stage and help you accelerate machine learning initiatives to achieve measurable results.

Download the 6 steps to machine learning success eBook to explore how organisations are unlocking the value of ML.

"In the future, we’re really looking forward to leverage the full power of (Amazon) SageMaker…to allow us to fundamentally change the product experience for our users."

Nhung Ho, VP of AI, Intuit

ML - 1

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