AWS Machine Learning Blog

AUGUST 7, 2023

In an effort to create and maintain a socially responsible gaming environment, AWS Professional Services was asked to build a mechanism that detects inappropriate language (toxic speech) within online gaming player interactions. Unfortunately, as in the real world, not all players communicate appropriately and respectfully.

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Data Science 101

NOVEMBER 7, 2019

It is now possible to deploy an Azure SQL Database to a virtual machine running on Amazon Web Services (AWS) and manage it from Azure. Azure Machine Learning is an environment to help with all the aspects of data science from data cleaning to model training to deployment. It’s true, I saw it happen this week.

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AWS Machine Learning Blog

APRIL 9, 2024

In the following sections, we explain how you can use these features with either the AWS Management Console or SDK. The correct response for this query is “Amazon’s annual revenue increased from $245B in 2019 to $434B in 2022,” based on the documents in the knowledge base. We ask “What was the Amazon’s revenue in 2019 and 2021?”

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AWS Machine Learning Blog

OCTOBER 2, 2023

To facilitate the labeling and manage our workforce, we use Amazon SageMaker Ground Truth , a data labeling service that allows you to build and manage your own data labeling workflows and workforce. Orchestrating data labeling Finally, it’s time to automate and orchestrate each of the steps of our labeling pipeline!

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AWS Machine Learning Blog

SEPTEMBER 14, 2023

“Data locked away in text, audio, social media, and other unstructured sources can be a competitive advantage for firms that figure out how to use it“ Only 18% of organizations in a 2019 survey by Deloitte reported being able to take advantage of unstructured data. The majority of data, between 80% and 90%, is unstructured data.

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AWS Machine Learning Blog

NOVEMBER 1, 2024

About the Authors Yanyan Zhang is a Senior Generative AI Data Scientist at Amazon Web Services, where she has been working on cutting-edge AI/ML technologies as a Generative AI Specialist, helping customers use generative AI to achieve their desired outcomes. Outside of work, she loves traveling, working out, and exploring new things.

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AWS Machine Learning Blog

MAY 15, 2023

We outline how we built an automated demand forecasting pipeline using Forecast and orchestrated by AWS Step Functions to predict daily demand for SKUs. On an ongoing basis, we calculate mean absolute percentage error (MAPE) ratios with product-based data, and optimize model and feature ingestion processes.

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AWS Machine Learning Blog

DECEMBER 1, 2023

Launched in 2019, Amazon SageMaker Studio provides one place for all end-to-end machine learning (ML) workflows, from data preparation, building and experimentation, training, hosting, and monitoring. Lauren Mullennex is a Senior AI/ML Specialist Solutions Architect at AWS. In his spare time, he loves traveling and writing.

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AWS Machine Learning Blog

SEPTEMBER 10, 2024

In this post, we detail our collaboration in creating two proof of concept (PoC) exercises around multi-modal machine learning for survival analysis and cancer sub-typing, using genomic (gene expression, mutation and copy number variant data) and imaging (histopathology slides) data. 2022 ) was implemented (Section 2.1).

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AWS Machine Learning Blog

JULY 3, 2024

To answer this question, the AWS Generative AI Innovation Center recently developed an AI assistant for medical content generation. 2019 Apr;179(4):561-569. Epub 2019 Jan 31. Data Scientist with 8+ years of experience in Data Science and Machine Learning. Am J Med Genet A. doi: 10.1002/ajmg.a.61055.

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AWS Machine Learning Blog

APRIL 6, 2023

& AWS Machine Learning Solutions Lab (MLSL) Machine learning (ML) is being used across a wide range of industries to extract actionable insights from data to streamline processes and improve revenue generation. We evaluated the WAPE for all BLs in the auto end market for 2019, 2020, and 2021.

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Dataconomy

SEPTEMBER 4, 2023

Organizations must diligently manage access controls, encryption, and data protection to mitigate risks. For example, the 2019 Capital One breach exposed over 100 million customer records, highlighting the need for robust security measures. Data catalog: Implement a data catalog to organize and catalog your data assets.

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AWS Machine Learning Blog

OCTOBER 25, 2023

In this blog post, we show you how you can use Sentinel 2 satellite imagery hosted on the AWS Registry of Open Data in combination with Amazon SageMaker geospatial capabilities to detect point sources of CH4 emissions and monitor them over time. About the authors Dr. Karsten Schroer is a Solutions Architect at AWS.

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Flipboard

FEBRUARY 2, 2023

Models were trained and cross-validated on the 2018, 2019, and 2020 seasons and tested on the 2021 season. Marc van Oudheusden is a Senior Data Scientist with the Amazon ML Solutions Lab team at Amazon Web Services. Marc van Oudheusden is a Senior Data Scientist with the Amazon ML Solutions Lab team at Amazon Web Services.

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AWS Machine Learning Blog

APRIL 19, 2023

Our data scientists train the model in Python using tools like PyTorch and save the model as PyTorch scripts. The steps are as follows: Training the models – Our data scientists train the models using PyTorch and save the models as torch scripts. The DJL was created at Amazon and open-sourced in 2019.

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AWS Machine Learning Blog

SEPTEMBER 19, 2023

The SageMaker Feature Store Feature Processor reduces this burden by automatically transforming raw data into aggregated features suitable for batch training ML models. It lets engineers provide simple data transformation functions, then handles running them at scale on Spark and managing the underlying infrastructure.

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AWS Machine Learning Blog

FEBRUARY 10, 2023

Advances in neural information processing systems 32 (2019). Visualizing data using t-SNE.” Mohamad Al Jazaery is an applied scientist at Amazon Machine Learning Solutions Lab. Prior to AWS, he obtained his MCS from West Virginia University and worked as computer vision researcher at Midea. “The Illustrated Transformer.”

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phData

NOVEMBER 8, 2024

Each snapshot has a separate manifest file that keeps track of the data files associated with that snapshot and hence can be restored/queries whenever needed. Versioning also ensures a safer experimentation environment, where data scientists can test new models or hypotheses on historical data snapshots without impacting live data.

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phData

JANUARY 31, 2024

Applying Machine Learning with Snowpark Now that we have our data from the Snowflake Marketplace, it’s time to leverage Snowpark to apply machine learning. Python has long been the favorite programming language of data scientists. The marketplace serves as a source of third-party data to supplement your internal datasets.

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Snorkel AI

MAY 24, 2023

chief data scientist, a role he held under President Barack Obama from 2015 to 2017. Bush, and has co-authored several books on data science. He received the 2014 ACM Doctoral Dissertation Award and the 2019 Presidential Early Career Award for Scientists and Engineers for his research on large-scale computing.

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Snorkel AI

MAY 24, 2023

chief data scientist, a role he held under President Barack Obama from 2015 to 2017. Bush, and has co-authored several books on data science. He received the 2014 ACM Doctoral Dissertation Award and the 2019 Presidential Early Career Award for Scientists and Engineers for his research on large-scale computing.

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Women in Big Data

JULY 10, 2023

She finished her second Masters in Computer Engineering and Cybersecurity in 2019 from San Jose State University. From forensic experts, behavioral science experts, background investigators, social engineering experts to data scientists, data analysts, software/malware engineers, there is demand and place for all.

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The MLOps Blog

AUGUST 3, 2023

Stefan is a software engineer, data scientist, and has been doing work as an ML engineer. He also ran the data platform in his previous company and is also co-creator of open-source framework, Hamilton. For example, let’s take Airflow , AWS SageMaker pipelines. I also recently found out, you are the CEO of DAGWorks.

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The MLOps Blog

MARCH 20, 2023

These practices are essential for data scientists, data engineers, or machine learning engineers to provide a comprehensive guide for managing dataset versions in a project that is supposed to run for a long time. Data Management at Scale. This section explores best practices that address these challenges.

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Mlearning.ai

JUNE 28, 2023

This is the highest accuracy achieved by fine-tuning the model on AWS SageMaker with the training data of 30,000 sentences between sentences 40,000 and 70,000. I also got a lot more comfortable with working with huge data and therefore master the skills of a data scientist along the way.

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Snorkel AI

MAY 25, 2023

Data scientists and researchers train LLMs on enormous amounts of unstructured data through self-supervised learning. BERT, the first breakout large language model In 2019, a team of researchers at Goole introduced BERT (which stands for bidirectional encoder representations from transformers).

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Snorkel AI

MAY 25, 2023

Data scientists and researchers train LLMs on enormous amounts of unstructured data through self-supervised learning. BERT, the first breakout large language model In 2019, a team of researchers at Goole introduced BERT (which stands for bidirectional encoder representations from transformers).

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Smart Data Collective

JUNE 22, 2025

More Read How BI & Data Analytics Pros Used Twitter in May Pageviews are Dead, Engagement is King Can AI Help You Get Better Headshots? There are not many industries left untouched by this trend. Followers Like 33.7k Followers Like 33.7k

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Hacker News

JULY 1, 2025

On the backend we're using 100% Go with AWS primitives. Stack : Python/Django, JavaScript, VueJS, PostgreSQL, Snowflake, Docker, Git, AWS, AI/LLM integrations (OpenAI & Gemini). My last startup, Bayes, went through YC in 2019. Profitable, 15+ yrs stable, 100% employee-owned. Based in NYC (Chinatown).

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IBM Journey to AI blog

JULY 19, 2023

In this blog post, we will showcase how IBM Consulting is partnering with AWS and leveraging Large Language Models (LLMs), on IBM Consulting’s generative AI-Automation platform (ATOM), to create industry-aware, life sciences domain-trained foundation models to generate first drafts of the narrative documents, with an aim to assist human teams.

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AWS Machine Learning Blog

APRIL 11, 2023

It’s a fully managed on-demand service, integrated with SageMaker and other AWS services, and therefore creates and manages resources for you. Furthermore, Pipelines is supported by the SageMaker Python SDK , letting you track your data lineage and reuse steps by caching them to ease development time and cost.

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AWS Machine Learning Blog

FEBRUARY 5, 2024

According to health organizations such as the Centers for Disease Control and Prevention ( CDC ) and the World Health Organization ( WHO ), a spillover event at a wet market in Wuhan, China most likely caused the coronavirus disease 2019 (COVID-19). Janosch Woschitz is a Senior Solutions Architect at AWS, specializing in geospatial AI/ML.

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AWS Machine Learning Blog

OCTOBER 11, 2024

With the Amazon Bedrock serverless experience, you can experiment with and evaluate top foundation models (FMs) for your use cases, privately customize them with your data using techniques such as fine-tuning and RAG, and build agents that run tasks using enterprise systems and data sources. On the Domains page, open your domain.

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AWS Machine Learning Blog

NOVEMBER 11, 2024

Prerequisites To try out this solution using SageMaker JumpStart, you’ll need the following prerequisites: An AWS account that will contain all of your AWS resources. An AWS Identity and Access Management (IAM) role to access SageMaker. He is specialized in architecting AI/ML and generative AI services at AWS.

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