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

ODSC - Open Data Science

Developing NLP tools isn’t so straightforward, and requires a lot of background knowledge in machine & deep learning, among others. In a change from last year, there’s also a higher demand for those with data analysis skills as well. Having mastery of these two will prove that you know data science and in turn, NLP.

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Accelerate disaster response with computer vision for satellite imagery using Amazon SageMaker and Amazon Augmented AI

AWS Machine Learning Blog

AWS recently released Amazon SageMaker geospatial capabilities to provide you with satellite imagery and geospatial state-of-the-art machine learning (ML) models, reducing barriers for these types of use cases. In the following sections, we dive into each pipeline in more detail.

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How Sportradar used the Deep Java Library to build production-scale ML platforms for increased performance and efficiency

AWS Machine Learning Blog

The DJL is a deep learning framework built from the ground up to support users of Java and JVM languages like Scala, Kotlin, and Clojure. With the DJL, integrating this deep learning is simple. Business requirements We are the US squad of the Sportradar AI department. The architecture of DJL is engine agnostic.

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The Data Dilemma: Exploring the Key Differences Between Data Science and Data Engineering

Pickl AI

Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. Data Visualization: Matplotlib, Seaborn, Tableau, etc.

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

Flipboard

Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and ML to deliver the best price-performance at any scale. To do this, we provide an AWS CloudFormation template to create a stack that contains the resources.

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How HR Tech Company Sense Scaled their ML Operations using Iguazio

Iguazio

The system’s architecture ensures the data flows through the different systems effectively. First, the data lake is fed from a number of data sources. These include conversational data, ATS Data and more. Sense onboarded Iguazio as an MLOps solution for the ML training and serving component of the pipeline.

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How Sense Uses Iguazio as a Key Component of Their ML Stack

Iguazio

The system’s architecture ensures the data flows through the different systems effectively. First, the data lake is fed from a number of data sources. These include conversational data, ATS data, and more. Sense onboarded Iguazio as an MLOps platform for the ML training and serving component of the pipeline.

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