Remove AWS Remove Natural Language Processing Remove SQL
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Remote Data Science Jobs: 5 High-Demand Roles for Career Growth

Data Science Dojo

For instance, Berkeley’s Division of Data Science and Information points out that entry level data science jobs remote in healthcare involves skills in NLP (Natural Language Processing) for patient and genomic data analysis, whereas remote data science jobs in finance leans more on skills in risk modeling and quantitative analysis.

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Transforming financial analysis with CreditAI on Amazon Bedrock: Octus’s journey with AWS

AWS Machine Learning Blog

We walk through the journey Octus took from managing multiple cloud providers and costly GPU instances to implementing a streamlined, cost-effective solution using AWS services including Amazon Bedrock, AWS Fargate , and Amazon OpenSearch Service. Along the way, it also simplified operations as Octus is an AWS shop more generally.

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Explore data with ease: Use SQL and Text-to-SQL in Amazon SageMaker Studio JupyterLab notebooks

AWS Machine Learning Blog

In the process of working on their ML tasks, data scientists typically start their workflow by discovering relevant data sources and connecting to them. They then use SQL to explore, analyze, visualize, and integrate data from various sources before using it in their ML training and inference.

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Build a robust text-to-SQL solution generating complex queries, self-correcting, and querying diverse data sources

AWS Machine Learning Blog

Structured Query Language (SQL) is a complex language that requires an understanding of databases and metadata. Today, generative AI can enable people without SQL knowledge. The solution in this post aims to bring enterprise analytics operations to the next level by shortening the path to your data using natural language.

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Achieve ~2x speed-up in LLM inference with Medusa-1 on Amazon SageMaker AI

AWS Machine Learning Blog

Large language models (LLMs) have revolutionized the field of natural language processing with their ability to understand and generate humanlike text. For details, refer to Creating an AWS account. Be sure to set up your AWS Command Line Interface (AWS CLI) credentials correctly.

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Boosting RAG-based intelligent document assistants using entity extraction, SQL querying, and agents with Amazon Bedrock

AWS Machine Learning Blog

Overview of RAG RAG solutions are inspired by representation learning and semantic search ideas that have been gradually adopted in ranking problems (for example, recommendation and search) and natural language processing (NLP) tasks since 2010.

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Generating value from enterprise data: Best practices for Text2SQL and generative AI

AWS Machine Learning Blog

One such area that is evolving is using natural language processing (NLP) to unlock new opportunities for accessing data through intuitive SQL queries. Instead of dealing with complex technical code, business users and data analysts can ask questions related to data and insights in plain language.

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