Tag: Apache Spark
Databricks claims its open source LLM outsmarts GPT-3.5
Analytics platform Databricks has launched an open source foundational large language model, hoping enterprises will opt to use its tools to jump on the...
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Databricks to absorb Arcion Labs for its data access tools
Analytics biz Databricks is set to purchase Arcion Labs, developer of a cloud-native data replication platform, in a deal estimated to be worth upwards...
How Meesho built a generalized feed ranker using Amazon SageMaker inference | Amazon Web Services
This is a guest post co-written by Rama Badrinath, Divay Jindal and Utkarsh Agrawal at Meesho. Meesho is India’s fastest growing ecommerce company...
Automatically redact PII for machine learning using Amazon SageMaker Data Wrangler | Amazon Web Services
Customers increasingly want to use deep learning approaches such as large language models (LLMs) to automate the extraction of data and insights. For many...
Microsoft Azure HDInsight Plagued With XSS Vulnerabilities
Microsoft, already under scrutiny for its cloud security practices, recently patched as many as eight severe vulnerabilities in various Apache services in Azure HDInsight...
Details on Google’s AI updates to cloud infrastructure
Cloud Next Google is razor-sharp-focused on AI at this year's Cloud Next, with a slew of hardware projects, including TPU updates, GPU options, and...
Apply fine-grained data access controls with AWS Lake Formation in Amazon SageMaker Data Wrangler | Amazon Web Services
Amazon SageMaker Data Wrangler reduces the time it takes to collect and prepare data for machine learning (ML) from weeks to minutes. You can...
Host the Spark UI on Amazon SageMaker Studio | Amazon Web Services
Amazon SageMaker offers several ways to run distributed data processing jobs with Apache Spark, a popular distributed computing framework for big data processing. You...
Accelerate time to business insights with the Amazon SageMaker Data Wrangler direct connection to Snowflake | Amazon Web Services
Amazon SageMaker Data Wrangler is a single visual interface that reduces the time required to prepare data and perform feature engineering from weeks to...
Build machine learning-ready datasets from the Amazon SageMaker offline Feature Store using the Amazon SageMaker Python SDK | Amazon Web Services
Amazon SageMaker Feature Store is a purpose-built service to store and retrieve feature data for use by machine learning (ML) models. Feature Store provides...
Use Amazon SageMaker Canvas to build machine learning models using Parquet data from Amazon Athena and AWS Lake Formation | Amazon Web Services
Data is the foundation for machine learning (ML) algorithms. One of the most common formats for storing large amounts of data is Apache Parquet...
Securing MLflow in AWS: Fine-grained access control with AWS native services
With Amazon SageMaker, you can manage the whole end-to-end machine learning (ML) lifecycle. It offers many native capabilities to help manage ML workflows aspects,...
Authoring custom transformations in Amazon SageMaker Data Wrangler using NLTK and SciPy
“Instead of focusing on the code, companies should focus on developing systematic engineering practices for improving data in ways that are reliable, efficient, and...
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