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Modernizing data science lifecycle management with AWS and Wipro

AWS Machine Learning

By the end of the consulting engagement, the team had implemented the following architecture that effectively addressed the core requirements of the customer team, including: Code Sharing – SageMaker notebooks enable data scientists to experiment and share code with other team members.

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Optimize pet profiles for Purina’s Petfinder application using Amazon Rekognition Custom Labels and AWS Step Functions

AWS Machine Learning

The solution uses the following services: Amazon API Gateway is a fully managed service that makes it easy for developers to publish, maintain, monitor, and secure APIs at any scale. Purina’s solution is deployed as an API Gateway HTTP endpoint, which routes the requests to obtain pet attributes.

APIs 101
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Highlight text as it’s being spoken using Amazon Polly

AWS Machine Learning

The text can be input from the browser or through an API call to the endpoint exposed by our solution. This calls an API (3) through Amazon API Gateway , to invoke an AWS Lambda function (4). The events invoke a callback function, which is another JavaScript function used to highlight the spoken text in the browser.

APIs 70
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Create powerful self-service experiences with Amazon Lex on Talkdesk CX Cloud contact center

AWS Machine Learning

Tasks like account balance lookups are completed in seconds, a 90% reduction in time compared to WaFd’s legacy system. How Talkdesk integrates with Amazon Lex When the call reaches Talkdesk Virtual Agent , Talkdesk uses the continuous streaming capability of the Amazon Lex API to enable conversation with the Amazon Lex bot.

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Manage your Amazon Lex bot via AWS CloudFormation templates

AWS Machine Learning

Similarly, you can use a Lambda function for fulfillment as well, for example writing data to databases or calling APIs save the collected information. Rijeesh Akkambeth Chathoth is a Professional Services Consultant at AWS. For more information, refer to Enabling custom logic with AWS Lambda functions.

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Reduce food waste to improve sustainability and financial results in retail with Amazon Forecast

AWS Machine Learning

After data is loaded to Amazon S3, an S3 event triggers AWS Lambda and invokes AWS Step Functions as an orchestration tool. We can then call a Forecast API to create a dataset group and import data from the processed S3 bucket. We use the AutoPredictor API, which is also accessible through the Forecast console.

APIs 98
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Build and train computer vision models to detect car positions in images using Amazon SageMaker and Amazon Rekognition

AWS Machine Learning

Finally, we show how you can integrate this car pose detection solution into your existing web application using services like Amazon API Gateway and AWS Amplify. For each option, we host an AWS Lambda function behind an API Gateway that is exposed to our mock application. split(",")[-1] body_bytes = base64.b64decode(body_bytes)

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