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Modernizing data science lifecycle management with AWS and Wipro

AWS Machine Learning

Many organizations have been using a combination of on-premises and open source data science solutions to create and manage machine learning (ML) models. Data science and DevOps teams may face challenges managing these isolated tool stacks and systems. Wipro is an AWS Premier Tier Services Partner and Managed Service Provider (MSP).

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Configure an AWS DeepRacer environment for training and log analysis using the AWS CDK

AWS Machine Learning

According to Accenture , companies that manage to efficiently scale AI and ML can achieve nearly triple the return on their investments. In this post, we enable the provisioning of different components required for performing log analysis using Amazon SageMaker on AWS DeepRacer via AWS CDK constructs.

Scripts 73
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Use RAG for drug discovery with Knowledge Bases for Amazon Bedrock

AWS Machine Learning

It allows you to seamlessly customize your RAG prompts and retrieval strategies—we provide the source attribution, and we handle memory management automatically. To enable effective retrieval from private data, a common practice is to first split these documents into manageable chunks. Choose Next. Choose Next.

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Connecting Amazon Redshift and RStudio on Amazon SageMaker

AWS Machine Learning

Last year, we announced the general availability of RStudio on Amazon SageMaker , the industry’s first fully managed RStudio Workbench integrated development environment (IDE) in the cloud. Users can also interact with data with ODBC, JDBC, or the Amazon Redshift Data API. There is no need to set up and manage clusters.

APIs 106
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Top 10 Auto Dialer Software in 2024 for Efficient Sales Teams

JustCall

Automation features and open API: An auto dialer offers open APIs so your developers can- – Build automation workflows for call logging, – Build workflows for notes logging – Help with reporting and analytics tasks (i.e., Open API for custom integrations and workflows. creating visualizations such as charts).

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Simplify continuous learning of Amazon Comprehend custom models using Comprehend flywheel

AWS Machine Learning

Amazon Comprehend is a managed AI service that uses natural language processing (NLP) with ready-made intelligence to extract insights about the content of documents. Flywheel creates a data lake (in Amazon S3) in your account where all the training and test data for all versions of the model are managed and stored.

APIs 68
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Reduce the time taken to deploy your models to Amazon SageMaker for testing

AWS Machine Learning

SageMaker is a fully managed machine learning (ML) service. Additionally, you don’t need to manage servers. You can perform data analysis, train your models, and test them using your own algorithms or use SageMaker-provided ML algorithms that are optimized to run efficiently against large datasets spread across multiple machines.

Scripts 74