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Learn Data Analysis with Julia

KDnuggets

Setup the environment, load the data, perform data analysis and visualization, and create the data pipeline all using Julia programming language.

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A Guide to Data Analysis in Python with DuckDB

KDnuggets

Learn how to perform data analysis in Python using DuckDB.

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All About AI-powered Data Analysis with Vizly

Analytics Vidhya

Now, imagine a world where […] The post All About AI-powered Data Analysis with Vizly appeared first on Analytics Vidhya. It has become a part of every major sector, from tech and healthcare to finance and entertainment, and continues transforming our work.

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Guide to Academic Data Analysis With Julius AI

Analytics Vidhya

However, with the right approach and tools, transforming data into meaningful knowledge is an immensely rewarding experience. In this guide, we will walk you through a typical academic data analysis workflow, […] The post Guide to Academic Data Analysis With Julius AI appeared first on Analytics Vidhya.

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Drive Better Decision-Making with Data Storytelling

Data-driven storytelling could be used to influence user actions, and ensure they understand what data matters the most. A good data story is formed by three components: Data analysis - This is the basis of a strong story and mastering the data is an essential part of the process.

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What is Exploratory Data Analysis (EDA) and How Does it Work?

Analytics Vidhya

Introduction Exploratory Data Analysis (EDA) is a process of describing the data by means of statistical and visualization techniques in order to bring important aspects of that data into focus for further analysis. appeared first on Analytics Vidhya.

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An Introduction to Julia for Data Analysis

Analytics Vidhya

Introduction Which language do we use when it comes to data analysis? But there is one more language for data analysis which is growing rapidly. The post An Introduction to Julia for Data Analysis appeared first on Analytics Vidhya. Of course, Python, isn’t it?

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How to Build Data Experiences for End Users

Data literate: Users have a comfort level of working with, manipulating, analyzing, and visualizing data. Data aware: Users can combine past experiences, intuition, judgment, and qualitative inputs and data analysis to make decisions. Download the eBook to learn about How to Build Data Experiences for End Users.