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What Are AI Credits and How Can Data Scientists Use Them?

ODSC - Open Data Science

Confluent Confluent provides a robust data streaming platform built around Apache Kafka. AI credits from Confluent can be used to implement real-time data pipelines, monitor data flows, and run stream-based ML applications. Modal Modal offers serverless compute tailored for data-intensive workloads.

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How Thomson Reuters delivers personalized content subscription plans at scale using Amazon Personalize

AWS Machine Learning Blog

TR used AWS Glue DataBrew and AWS Batch jobs to perform the extract, transform, and load (ETL) jobs in the ML pipelines, and SageMaker along with Amazon Personalize to tailor the recommendations. Then the events are ingested into TR’s centralized streaming platform, which is built on top of Amazon Managed Streaming for Kafka (Amazon MSK).

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Discover the Most Important Fundamentals of Data Engineering

Pickl AI

They are responsible for building and maintaining data architectures, which include databases, data warehouses, and data lakes. Their work ensures that data flows seamlessly through the organisation, making it easier for Data Scientists and Analysts to access and analyse information.

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The Backbone of Data Engineering: 5 Key Architectural Patterns Explained

Mlearning.ai

There are various architectural design patterns in data engineering that are used to solve different data-related problems. This article discusses five commonly used architectural design patterns in data engineering and their use cases. Finally, the transformed data is loaded into the target system.

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How data engineers tame Big Data?

Dataconomy

They are responsible for designing, building, and maintaining the infrastructure and tools needed to manage and process large volumes of data effectively. This involves working closely with data analysts and data scientists to ensure that data is stored, processed, and analyzed efficiently to derive insights that inform decision-making.

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Why Software Engineers Should Be Embracing AI: A Guide to Staying Ahead

ODSC - Open Data Science

Confirmed sessions related to software engineering include: Building Data Contracts with Open-Source Tools Chronon — Open Source Data Platform for AI/ML Creating APIs That Data Scientists Will Love with FastAPI, SQLAlchemy, and Pydantic Using APIs in Data Science Without Breaking Anything Don’t Go Over the Deep End: Building an Effective OSS Management (..)

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7 Best Machine Learning Workflow and Pipeline Orchestration Tools 2024

DagsHub

Image generated with Midjourney In today’s fast-paced world of data science, building impactful machine learning models relies on much more than selecting the best algorithm for the job. Data scientists and machine learning engineers need to collaborate to make sure that together with the model, they develop robust data pipelines.