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Unstructured Data: Examples, Tools, Techniques, and Best Practices

AltexSoft

In today’s data-driven world, organizations amass vast amounts of information that can unlock significant insights and inform decision-making. A staggering 80 percent of this digital treasure trove is unstructured data, which lacks a pre-defined format or organization. What is unstructured data?

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Top 16 Data Science Specializations of 2024 + Tips to Choose

Knowledge Hut

Professionals from a variety of disciplines use data in their day-to-day operations and feel the need to understand cutting-edge technology to get maximum insights from the data, therefore contributing to the growth of the organization. A Data Engineer's primary responsibility is the construction and upkeep of a data warehouse.

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Audio Analysis With Machine Learning: Building AI-Fueled Sound Detection App

AltexSoft

Aiming at understanding sound data, it applies a range of technologies, including state-of-the-art deep learning algorithms. Audio analysis has already gained broad adoption in various industries, from entertainment to healthcare to manufacturing. Audio data file formats. Audio data analysis steps.

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Data Scientist roles and responsibilities

U-Next

A high-ranking expert is known as a “Data Scientist” who works with big data and has the mathematics, economic, technical, analytic, and technological abilities necessary to cleanse, analyse and evaluate organised and unstructured data to help organisations make more informed decisions.

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15 Top Machine Learning Projects for Final Year Students

ProjectPro

It is because these apps render machine learning models that try to understand the customer's taste. Recommendation engines are popular in media, entertainment, and shopping. To build such ML projects, you must know different approaches to cleaning raw data. Modern e-commerce sites like Flipkart, Amazon, Alibaba, etc.,

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20 Solved End-to-End Big Data Projects with Source Code

ProjectPro

A big data project is a data analysis project that uses machine learning algorithms and different data analytics techniques on a large dataset for several purposes, including predictive modeling and other advanced analytics applications. To build a big data project, you should always adhere to a clearly defined workflow.