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How to Manage Unstructured Data in AI and Machine Learning Projects

DagsHub

For instance, if the collected data was a text document in the form of a PDF, the data preprocessing—or preparation stage —can extract tables from this document. The pipeline in this stage can convert the document into CSV files, and you can then analyze it using a tool like Pandas. Unstructured.io

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A Comprehensive Guide to the main components of Big Data

Pickl AI

This includes structured data (like databases), semi-structured data (like XML files), and unstructured data (like text documents and videos). Data processing frameworks, such as Apache Hadoop and Apache Spark, are essential for managing and analysing large datasets.

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A Comprehensive Guide to the Main Components of Big Data

Pickl AI

This includes structured data (like databases), semi-structured data (like XML files), and unstructured data (like text documents and videos). Data processing frameworks, such as Apache Hadoop and Apache Spark, are essential for managing and analysing large datasets.

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Introduction to R Programming For Data Science

Pickl AI

These packages allow for text preprocessing, sentiment analysis, topic modeling, and document classification. Packages like dplyr, data.table, and sparklyr enable efficient data processing on big data platforms such as Apache Hadoop and Apache Spark.

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Web Scraping vs. Web Crawling: Understanding the Differences

Pickl AI

Apache Nutch A powerful web crawler built on Apache Hadoop, suitable for large-scale data crawling projects. Nutch is often used in conjunction with other Hadoop tools for big data processing. Beautiful Soup A Python library for parsing HTML and XML documents.

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Beginner’s Guide To GCP BigQuery (Part 1)

Mlearning.ai

In my 7 years of Data Science journey, I’ve been exposed to a number of different databases including but not limited to Oracle Database, MS SQL, MySQL, EDW, and Apache Hadoop. A well designed database utilizes views at the right place and at the right time.

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Best Resources for Kids to learn Data Science with Python

Pickl AI

Accordingly, it is possible for the Python users to ask for help from Stack Overflow, mailing lists and user-contributed code and documentation. Big Data Technologies: As the amount of data grows, familiarity with big data technologies such as Apache Hadoop, Apache Spark, and distributed computer platforms might be useful.