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Basic Data Science Terms Every Data Analyst Should Know

Pickl AI

Summary : This article equips Data Analysts with a solid foundation of key Data Science terms, from A to Z. Introduction In the rapidly evolving field of Data Science, understanding key terminology is crucial for Data Analysts to communicate effectively, collaborate effectively, and drive data-driven projects.

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Data science vs. machine learning: What’s the difference?

IBM Journey to AI blog

The fields have evolved such that to work as a data analyst who views, manages and accesses data, you need to know Structured Query Language (SQL) as well as math, statistics, data visualization (to present the results to stakeholders) and data mining.

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Understanding the Synergy Between Artificial Intelligence & Data Science

Pickl AI

Synergy Between Artificial Intelligence and Data Science AI and Data Science complement each other through their unique but interconnected roles in data processing and analysis. Data Science involves extracting insights from structured and unstructured data using statistical methods, data mining, and visualisation techniques.

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Unleashing the Power of Applied Text Mining in Python: Revolutionize Your Data Analysis

Pickl AI

Future directions in text mining include improving language understanding with the help of deep learning models, developing better techniques for multilingual text analysis, and integrating text mining with other domains like image and video analysis. Frequently Asked Questions How does text mining differ from data mining?