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...

Data is everywhere, and it comes in large amounts. Making sense of it all can lead to amazing discoveries and better business decisions. Yet,...

Amazon SageMaker Pipelines is a fully managed AWS service for building and orchestrating machine learning (ML) workflows. SageMaker Pipelines offers ML application developers the...

Amazon SageMaker Data Wrangler reduces the time it takes to collect and prepare data for machine learning (ML) from weeks to minutes. You can...

Amazon SageMaker offers several ways to run distributed data processing jobs with Apache Spark, a popular distributed computing framework for big data processing. You...

Data is the foundation for machine learning (ML) algorithms. One of the most common formats for storing large amounts of data is Apache Parquet...

In 2021, we launched AWS Support Proactive Services as part of the AWS Enterprise Support offering. Since its introduction, we have helped hundreds of...

Amazon SageMaker provides a broad selection of machine learning (ML) infrastructure and model deployment options to help meet your ML inference needs. It’s a...

Jupyter notebooks are highly favored by data scientists for their ability to interactively process data, build ML models, and test these models by making...

Serving a large user base with reliable, consistent and low latency data is a very hard challenge for any backend team. At Ledger, we...

Each machine learning (ML) system has a unique service level agreement (SLA) requirement with respect to latency, throughput, and cost metrics. With advancements in...

RStudio on Amazon SageMaker is the industry’s first fully managed RStudio Workbench integrated development environment (IDE) in the cloud. You can quickly launch the...