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Augmented analytics

Dataconomy

Augmented analytics is revolutionizing how organizations interact with their data. By harnessing the power of machine learning (ML) and natural language processing (NLP), businesses can streamline their data analysis processes and make more informed decisions. What is augmented analytics?

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Interesting NLP Use Cases Every Data Science Enthusiast should know!

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Natural Language Processing (NLP) is a subpart of Artificial Intelligence. appeared first on Analytics Vidhya. The post Interesting NLP Use Cases Every Data Science Enthusiast should know!

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5 Error Handling Patterns in Python (Beyond Try-Except)

KDnuggets

By subscribing you accept KDnuggets Privacy Policy Leave this field empty if youre human: Get the FREE ebook The Great Big Natural Language Processing Primer and The Complete Collection of Data Science Cheat Sheets along with the leading newsletter on Data Science, Machine Learning, AI & Analytics straight to your inbox.

Python 173
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Generative AI for Data Analytics: Top 7 Tools, Use-cases, and More

Data Science Dojo

Generative AI (GenAI) is stepping in to change the game by making data analytics accessible to everyone. As data keeps growing, tools powered by Generative AI for data analytics are helping businesses and individuals tap into this potential, making decisions faster and smarter.

Analytics 195
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Natural Language Query (NLQ)

Dataconomy

Natural Language Query (NLQ) is changing the way we interact with data analytics by allowing users to speak or type their questions in a way that feels natural and intuitive. Natural Language Query (NLQ) enables users to query databases using everyday language rather than specialized query languages like SQL.

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Remote Data Science Jobs: 5 High-Demand Roles for Career Growth

Data Science Dojo

For instance, Berkeley’s Division of Data Science and Information points out that entry level data science jobs remote in healthcare involves skills in NLP (Natural Language Processing) for patient and genomic data analysis, whereas remote data science jobs in finance leans more on skills in risk modeling and quantitative analysis.

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Business Analytics vs Data Science: Which One Is Right for You?

Pickl AI

Summary: Business Analytics focuses on interpreting historical data for strategic decisions, while Data Science emphasizes predictive modeling and AI. Introduction In today’s data-driven world, businesses increasingly rely on analytics and insights to drive decisions and gain a competitive edge. What is Business Analytics?