Home Opinions & Editorials Events AWS Summit Madrid 2019 highlighted Machine Learning

AWS Summit Madrid 2019 highlighted Machine Learning

-

AWS Summit Madrid 2019 was just another fruitful event for the enterprises and developers as new announcements brought in excitement. AWS Summits are always focused on community building and providing a common platform for all cloud innovations. In Madrid, organizations shared their success stories leveraging AWS cloud.

AWS Summit Madrid introduced existing and new services to local potential customers in Spain. If you have missed the event, here is the entire summary of the announcements that raised our eyebrows.

Databases scaling enterprises’ ability to handle data

In the summit, machine learning grabbed all the attention. The database success stories also put enterprises in confidence for what to do with huge and complex data.

Cespa, a global energy company, presented their success story for building the data lakes from scratch. Cespa encountered a problem that many companies face. The problem was how to handle complex data that they were collecting. Their innovative approach of building data lakes with AWS helped them tackle and analyze the big data.

AWS is ready to go all the way for ML

AWS Summit Madrid is one of the few events where AWS confidently discussed ML with their services. All new updates regarding services which support machine learning also paved the way for more customer-centric products and services.

Amazon Machine Learning algorithm discovers pattern & data; and constructs the mathematical model using this data. These models are used to make predictions in new data. Machine Learning can be implemented in an ample amount of applications.

AWS Machine Learning helps the user to quickly build smart applications that can help to perform important tasks such as fraud detection, demand forecasting, predictive customer support, and quick prediction. Amazon Machine Learning synchronizes the previous data and utilizes it further to provide the necessary information to the user.

There were 8 new AWS Machine Learning announcements made in this event. Let’s discuss them one by one:

Open Platform

Machine Learning is suitable for the data researcher, M/L researcher, or developer. AWS offers Machine Learning services and tools tailored to fulfil your wants and level of expertise.

API-Driven Machine Learning Service

Developers will simply add intelligence to any application with various choice of pre-trained services that give computer vision, speech, language analysis, and chatbot practicality.

Framework Support

AWS supports all the most important Machine Learning frameworks, together with TensorFlow, Caffe2, and Apache MXNet, so you’ll bring or develop any model you select.

Broad Computing Choices

AWS offers a broad array of computing choices for coaching and inference with powerful GPU-based instances, compute and memory optimized instances, and even FPGAs.

Deep Platform Integrations

ML services are deeply integrated with the rest of the platform together with the data lake and database tools you wish to run Machine Learning workloads. The data on AWS offers you access to a powerful and complete platform for large data.

Comprehensive Analytics

Choose from a comprehensive set of services for data analysis together with data storage, business intelligence, batch processing, stream process, data progress orchestration.

Secure

Control access to resources with granular permission policies. Storage and database services provide sturdy coding to stay your data secure. Versatile key management choices enable you to settle on whether or not you or AWS can manage the encryption keys.

Economical

Consume services as you wish them and just for the amount you utilize them. AWS pricing has no direct fees, termination penalties, or future contracts. The AWS Free Tier helps you start with AWS.

Additional Services you can combine with Machine Learning:

Sagemaker

Amazon Sagemaker helps data scientists and developers very efficiently. It helps to build, train, and deploy Machine Learning models. Sagemaker has a new architecture which can help with all of its capabilities in your existing Machine Learning workflows.

DeepLens

It is a Deep Learning-enabled video camera, which is made for developers. Integrating this with Amazon Sagemaker will help to get up and running with Deep Learning quickly and easily.

Conclusion:

AWS Summit Madrid showed how AWS is looking to capture all the futuristic and innovative fields through cloud computing. Databases and M/L opens an entirely new approach to handle data and develop better applications respectively. The most interesting thing to pay close attention in the nearby future is how AWS’ counterparts present competition in this new race.

Cloud Evangelist
Cloud Evangelist
Cloud Evangelists are CMI's in house ambassadors for the entire Cloud ecosystem. They are responsible for propagating the doctrine of cloud computing and help community members make informed decisions.

Cloud

Cloud Management