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Discovering the Role of Data Science in a Cloud World

Pickl AI

Summary: “Data Science in a Cloud World” highlights how cloud computing transforms Data Science by providing scalable, cost-effective solutions for big data, Machine Learning, and real-time analytics. Advancements in data processing, storage, and analysis technologies power this transformation.

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Boost your MLOps efficiency with these 6 must-have tools and platforms

Data Science Dojo

Machine learning (ML) is the technology that automates tasks and provides insights. It allows data scientists to build models that can automate specific tasks. It comes in many forms, with a range of tools and platforms designed to make working with ML more efficient. It also has ML algorithms built into the platform.

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The 2021 Executive Guide To Data Science and AI

Applied Data Science

Automation Automating data pipelines and models ➡️ 6. The Data Engineer Not everyone working on a data science project is a data scientist. Data engineers are the glue that binds the products of data scientists into a coherent and robust data pipeline.

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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

Alignment to other tools in the organization’s tech stack Consider how well the MLOps tool integrates with your existing tools and workflows, such as data sources, data engineering platforms, code repositories, CI/CD pipelines, monitoring systems, etc. and Pandas or Apache Spark DataFrames.

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Top NLP Skills, Frameworks, Platforms, and Languages for 2023

ODSC - Open Data Science

Computer science, math, statistics, programming, and software development are all skills required in NLP projects. Cloud Computing, APIs, and Data Engineering NLP experts don’t go straight into conducting sentiment analysis on their personal laptops.

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Navigating the Cloud Modernization Journey: Insights from Precisely’s Partnership with AWS

Precisely

As a Technical Architect at Precisely, I’ve had the unique opportunity to lead the AWS Mainframe Modernization Data Replication for IBM i initiative, a project that not only challenged our technical capabilities but also enriched our understanding of cloud integration complexities.

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Deployment of Data and ML Pipelines for the Most Chaotic Industry: The Stirred Rivers of Crypto

The MLOps Blog

And we at deployr , worked alongside them to find the best possible answers for everyone involved and build their Data and ML Pipelines. Building data and ML pipelines: from the ground to the cloud It was the beginning of 2022, and things were looking bright after the lockdown’s end.

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