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Data Science & Analytics Industry Main Developments in 2021 and Key Trends for 2022

KDnuggets

We have solicited insights from experts at industry-leading companies, asking: "What were the main AI, Data Science, Machine Learning Developments in 2021 and what key trends do you expect in 2022?" Read their opinions here.

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Accelerating AI/ML development at BMW Group with Amazon SageMaker Studio

Flipboard

Data scientists and ML engineers require capable tooling and sufficient compute for their work. Therefore, BMW established a centralized ML/deep learning infrastructure on premises several years ago and continuously upgraded it.

ML 153
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How Carrier predicts HVAC faults using AWS Glue and Amazon SageMaker

AWS Machine Learning Blog

We first highlight how we use AWS Glue for highly parallel data processing. We then discuss how Amazon SageMaker helps us with feature engineering and building a scalable supervised deep learning model. Data processing and model inference need to scale as our data grows. Kexin Ding is a fifth-year Ph.D.

AWS 128
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Introducing watsonx: The future of AI for business

IBM Journey to AI blog

After some impressive advances over the past decade, largely thanks to the techniques of Machine Learning (ML) and Deep Learning , the technology seems to have taken a sudden leap forward. A data store built on open lakehouse architecture, it runs both on premises and across multi-cloud environments.

AI 110
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Build ML features at scale with Amazon SageMaker Feature Store using data from Amazon Redshift

Flipboard

Amazon Redshift is the most popular cloud data warehouse that is used by tens of thousands of customers to analyze exabytes of data every day. AWS Glue is a serverless data integration service that makes it easy to discover, prepare, and combine data for analytics, ML, and application development.

ML 123
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The Cloud Connection: How Governance Supports Security

Alation

This two-part series will explore how data discovery, fragmented data governance , ongoing data drift, and the need for ML explainability can all be overcome with a data catalog for accurate data and metadata record keeping. The Cloud Data Migration Challenge. Data pipeline orchestration.

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Advance environmental sustainability in clinical trials using AWS

AWS Machine Learning Blog

Instead, a core component of decentralized clinical trials is a secure, scalable data infrastructure with strong data analytics capabilities. Amazon Redshift is a fully managed cloud data warehouse that trial scientists can use to perform analytics.

AWS 117