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Tag: ML Model

Large-scale feature engineering with sensitive data protection using AWS Glue interactive sessions and Amazon SageMaker Studio

Organizations are using machine learning (ML) and AI services to enhance customer experience, reduce operational cost, and unlock new possibilities to improve business outcomes. Data underpins ML and AI use cases and is a strategic asset to an organization. As data is growing at an exponential rate, organizations are looking to set up an integrated, […]

How to choose a programming language for your machine learning project?

Looking for the best language for machine learning? If you’re new to the topic, the hardest part of mastering machine learning is figuring out...

Build a cross-account MLOps workflow using the Amazon SageMaker model registry

A well-designed CI/CD pipeline is essential to scale any software development workflow effectively. When designing production CI/CD pipelines, AWS recommends leveraging multiple accounts to isolate resources, contain security threats and simplify billing-and data science pipelines are no different. At AWS, we’re continuing to innovate to simplify the MLOps workflow. In this post, we discuss some […]

Enabling hybrid ML workflows on Amazon EKS and Amazon SageMaker with one-click Kubeflow on AWS deployment

Today, many AWS customers are building enterprise-ready machine learning (ML) platforms on Amazon Elastic Kubernetes Service (Amazon EKS) using Kubeflow on AWS (an AWS-specific...

If I Had To Start Learning Data Science Again, How Would I Do It?

Not long ago, I started thinking if I had to start learning machine learning and data science all over again, where would I start?...

How to Democratize Data Science

Efforts to democratize Data Science can be described as creating an environment that allows people with little expertise to perform Data Science research. This approach can be especially useful for businesses desperate to access the skills of a data scientist, but unable to hire one. A variety of user-friendly analytics tools have become available to support staff […]

The post How to Democratize Data Science appeared first on DATAVERSITY.

Detect multicollinearity, target leakage, and feature correlation with Amazon SageMaker Data Wrangler

In machine learning (ML), data quality has direct impact on model quality. This is why data scientists and data engineers spend significant amount of time perfecting training datasets. Nevertheless, no dataset is perfect—there are trade-offs to the preprocessing techniques such as oversampling, normalization, and imputation. Also, mistakes and errors could creep in at various stages […]

Refit trained parameters on large datasets using Amazon SageMaker Data Wrangler

Amazon SageMaker Data Wrangler helps you understand, aggregate, transform, and prepare data for machine learning (ML) from a single visual interface. It contains over 300 built-in data transformations so you can quickly normalize, transform, and combine features without having to write any code. Data science practitioners generate, observe, and process data to solve business problems […]

How Prodege saved $1.5 million in annual human review costs using low-code computer vision AI

This post was co-authored by Arun Gupta, the Director of Business Intelligence at Prodege, LLC. Prodege is a data-driven marketing and consumer insights platform comprised of consumer brands—Swagbucks, MyPoints, Tada, ySense, InboxDollars, InboxPounds, DailyRewards, PollFish, and Upromise—along with a complementary suite of business solutions for marketers and researchers. Prodege has 120 million users and has […]

Identifying and avoiding common data issues while building no code ML models with Amazon SageMaker Canvas

Business analysts work with data and like to analyze, explore, and understand data to achieve effective business outcomes. To address business problems, they often...

Brain tumor segmentation at scale using AWS Inferentia

Medical imaging is an important tool for the diagnosis and localization of disease. Over the past decade, collections of medical images have grown rapidly,...

Model Hosting Patterns in SageMaker: Best practices in testing and updating models on SageMaker

Amazon SageMaker is a fully managed service that provides developers and data scientists the ability to quickly build, train, and deploy machine learning (ML)...

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