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Shyam Prakash Mishra
Shyam Prakash Mishra

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AWS MACHINE LEARNING

What is AWS machine learning?
Amazon Machine Learning is a service offered by AWS that allows us to develop predictive applications by using algorithms, mathematical models based on the user’s data. Machine Learning can be implemented in an ample amount of applications. AWS Machine Learning help 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 reads data through Amazon S3, Redshift and RDS, then visualizes the data through the AWS Management Console and the Amazon Machine Learning API. This data can be imported or exported to other AWS services via S3 buckets. It uses β€œindustry-standard logistic regression” algorithm to generate models. AWS ML is used to review customer feedback in email, product reviews, forum, and phone transcripts. This further recommends the product action to the service team or connects the customer with customer care specialist. AWS Machine Learning is easy to use as the user can locate the data within Amazon Web Services.

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

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

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

4.More 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.

5.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
the foremost complete platform for large data.

6.API-Driven Machine Learning Service

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

7.Open Source Platform
Machine Learning is suitable for the data researcher, Machine Learning researcher, or developer. AWS offers Machine Learning services and tools tailored to fulfill your wants and level of expertise.

Advantages of AWS Machine Learning

Amazon’s AWS Machine Learning suite of services can help cut down the time and expense it typically takes to develop, test, and deploy ML models. For instance, adding specifics to pre-trained models can help a company quickly deploy a chatbot to help with customer service tasks. AWS also supports all of the major machine learning frameworks, such as TensorFlow and Caffe2.

It’s also secure, with end-to-end encryption, and provides a β€œpay-as-you-go” model that allows organizations of all sizes to
scale as needed. Also, AWS provides numerous data analysis
services to help make the best business decisions possible. A
known leader in cloud computing, Amazon offers a fantastic end
to-end solution for companies implementing machine learning into
their products, services, and operations.

References:https://aws.amazon.com/machine-learning/

Thanks For Reading!
Connect With Me on https://www.linkedin.com/in/shyam-prakash-mishra-5b53b6220

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