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A Beginner’s Guide to Structuring Data Science Project’s Workflow

Analytics Vidhya

Introduction Asides from dedication to discovery and exploration, to succeed in a Data Science project, you must understand the process and optimize it to ensure that the results are reliable and the project is easy to follow, maintain and modify where necessary. And […].

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From Unstructured to Structured Data with LLMs

KDnuggets

Learn how to use large language models to extract insights from documents for analytics and ML at scale. Join this webinar and live tutorial to learn how to get started.

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Synthetic Data Platforms: Unlocking the Power of Generative AI for Structured Data

KDnuggets

The article highlights various use cases of synthetic data, including generating confidential data, rebalancing imbalanced data, and imputing missing data points. It also provides information on popular synthetic data generation tools such as MOSTLY AI, SDV, and YData.

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Navigating Data Formats with Pandas for Beginners

Analytics Vidhya

Introduction Pandas is more than just a name – it’s short for “panel data.” Use the Data formats with pandas in economics and statistics. It refers to structured data sets that hold observations across multiple periods for different entities or subjects. ” Now, what exactly does that mean?

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Document Information Extraction Using Pix2Struct

Analytics Vidhya

Introduction Document information extraction involves using computer algorithms to extract structured data (like employee name, address, designation, phone number, etc.) from unstructured or semi-structured documents, such as reports, emails, and web pages.

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A Brief Introduction to Apache HBase and it’s Architecture

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Since the 1970s, relational database management systems have solved the problems of storing and maintaining large volumes of structured data.

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Understanding Neo4J: Comprehensive Guide for Data Enthusiasts

Analytics Vidhya

Introduction For decades the data management space has been dominated by relational databases(RDBMS); that’s why whenever we have been asked to store any volume of data, the default storage is RDBMS. But now we can’t think like that as we have a flood of unstructured or semi-structured data, which requires reliable technology.