Tag: Amazon SageMaker

As the old saying goes, “You never get a second chance to make a first impression.” Customer trust is hard-earned and easily lost. Properly architecting a scalable and secure SaaS-based product is just as important as feature development and sales. No one wants to fail on Day 1— you worked too hard to get there. Get a comprehensive introduction to the common ways in which customers consume cloud-based SaaS models, and explore the different ways in which ISVs sell their software products to customers.

Data scientists creating enterprise machine learning models to process large volumes of data spend a significant portion of their time managing the infrastructure required to process the data, rather than exploring the data and building ML models. You can reduce this overhead by running Qubole data processing tools and Amazon SageMaker. An open data lake platform, Qubole automates the administration and management of your resources on AWS.

Deploying AI solutions with ML models into production introduces new challenges. Machine Learning Operations (MLOps) has been evolving rapidly as the industry learns to marry new ML technologies and practices with incumbent software delivery systems and processes. WordStream is a SaaS company using ML capabilities to help small and mid-sized businesses get the most out of their online advertising. Learn how Slalom developed ML architecture to help WordStream productionize their machine learning efforts.

Amazon SageMaker provides all the components needed for machine learning in a single toolset. This allows ML models to get to production faster with much less effort and at lower cost. Learn about the data modeling process used by BizCloud Experts and the results they achieved for Neiman Marcus. Amazon SageMaker was employed to help develop and train ML algorithms for recommendation, personalization, and forecasting models that Neiman Marcus uses for data analysis and customer insights.

Voice data represents a rich and relatively untapped source of information that can help organizations gaining precious insights into their customers and operations. By leveraging a number of AWS services, Deloitte’s speech analytics solution, TrueVoice, can process voice data at scale, apply machine learning models to extract valuable information for this unstructured data, and continuously refine and enrich such models, tailoring them to specific industries and business needs.

Advances in the Industrial Internet of Things (IIoT) have made smart factories a reality through the application of AI and cloud computing technologies. In this post, explore how EXOR International’s systems-on-module (SOM) and edge gateways, powered by Intel’s Cyclone V FPGA, allow system integrators and application builders to deliver AWS-based IIoT solutions with faster time-to-market, lower total cost of ownership, and reduced development efforts.

With connected IoT solutions built on AWS, businesses can be more proactive with maintenance instead of reactionary, allowing them to fix problems with machinery before they become critical. Reliance Steel & Aluminum Co. teamed up with TensorIoT to solve for this use case. Together, they built an IoT solution on AWS that ensures the maintenance needs of Reliance’s industrial machinery are anticipated and that machines can be serviced before breaking down.

Time series forecasting is a common customer need. Amazon Forecast accelerates this and is based on the same technology used at Amazon.com. This new service massively reduces the effort required to automate data updating and model retraining, and it manages this while retaining the granularity of control that data scientists will appreciate and utilize. This post explores the use of this new service for energy consumption forecasting.

In today’s increasingly digital world, the nature and function of buildings is constantly changing. Facility managers face increasing pressure to adapt to an ever-evolving workplace and regulatory requirements while improving customer comforts and reducing operating costs. Learn about Cognizant’s smart building solution and why this APN Premier Consulting Partner chose AWS for hosting its application, as well as how AWS helps Cognizant fulfill commitments to customers.

We are often asked how to integrate software with Amazon SageMaker and use the service’s built-in machine learning algorithms. In this post, we discuss how to use the training capabilities of Amazon SageMaker to leverage its built-in algorithms. The types of applications that can integrate with Amazon SageMaker are data science platforms, business intelligence tools, or any application that needs to use machine learning behind the scenes.