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Deploying a Flask App on AWS Elastic Beanstalk

Analytics Vidhya

Image 1- [link] Whether you are an experienced or an aspiring data scientist, you must have worked on machine learning model development comprising of data cleaning, wrangling, comparing different ML models, training the models on Python Notebooks like Jupyter. All the […].

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Top 26 Data Science Tools for Data Scientists in 2024

Analytics Vidhya

Introduction The field of data science is evolving rapidly, and staying ahead of the curve requires leveraging the latest and most powerful tools available. In 2024, data scientists have a plethora of options to choose from, catering to various aspects of their work, including programming, big data, AI, visualization, and more.

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Build and deploy a UI for your generative AI applications with AWS and Python

AWS Machine Learning Blog

However, as exciting as these advancements are, data scientists often face challenges when it comes to developing UIs and to prototyping and interacting with their business users. Streamlit allows data scientists to create interactive web applications using Python, using their existing skills and knowledge.

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Building Generative AI and ML solutions faster with AI apps from AWS partners using Amazon SageMaker

AWS Machine Learning Blog

Introducing Amazon SageMaker partner AI apps Today, we’re excited to announce that AI apps from AWS Partners are now available in SageMaker. SageMaker AI makes sure that sensitive data stays completely within each customer’s SageMaker environment and will never be shared with a third party.

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An Introduction to AWS Sagemaker for Beginners

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction on AWS Sagemaker Data scientists need to create, train and deploy a large number of models as they work. AWS has created a simple […].

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How Crexi achieved ML models deployment on AWS at scale and boosted efficiency

AWS Machine Learning Blog

Customers are looking for success stories about how best to adopt the culture and new operational solutions to support their data scientists. Solution overview Central to Crexi’s infrastructure are boilerplate AWS Lambda triggers that call Amazon SageMaker endpoints, executing any given model’s inference logic asynchronously.

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AWS SageMaker

Dataconomy

AWS SageMaker is transforming the way organizations approach machine learning by providing a comprehensive, cloud-based platform that standardizes the entire workflow, from data preparation to model deployment. What is AWS SageMaker?

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