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How Exploratory Data Analysis Helped Me Solve Million-Dollar Business Problems

Towards AI

Photo by Luke Chesser on Unsplash EDA is a powerful method to get insights from the data that can solve many unsolvable problems in business. EDA is an iterative process, and is used to uncover hidden insights and uncover relationships within the data. Let me walk you through the definition of EDA in the form of a story.

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11 Open Source Data Exploration Tools You Need to Know in 2023

ODSC - Open Data Science

ydata-profiling GitHub | Website The primary goal of ydata-profiling is to provide a one-line Exploratory Data Analysis (EDA) experience in a consistent and fast solution. The tool is a full-stack BI platform, so analysts can write their metrics in-house, enabling the entire business to work with the data with ease.

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The project I did to land my business intelligence internship?—?CAR BRAND SEARCH

Mlearning.ai

The project I did to land my business intelligence internship — CAR BRAND SEARCH ETL PROCESS WITH PYTHON, POSTGRESQL & POWER BI 1. Submission Suggestions The project I did to land my business intelligence internship — CAR BRAND SEARCH was originally published in MLearning.ai imagine AI 3D Models Mlearning.ai

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Exploratory Data Analysis on Stock Market Data

Mlearning.ai

Exploratory Data Analysis on Stock Market Data Photo by Lukas Blazek on Unsplash Exploratory Data Analysis (EDA) is a crucial step in data science projects. In this tutorial, we will perform EDA on the S&P 500 dataset using Python. In this tutorial, we performed EDA on the S&P 500 dataset using Python. pct_change().dropna(),

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Data Analysis vs. Data Visualization – More Than Just Pretty Charts

Pickl AI

Exploratory Data Analysis (EDA): Using statistical summaries and initial visualisations (yes, visualisation plays a role within analysis!) EDA: Calculate overall churn rate. It involves handling missing values, correcting errors, removing duplicates, standardizing formats, and structuring data for analysis.

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Announcing the Winners of ‘The NFL Fantasy Football’ Data Challenge

Ocean Protocol

AI / ML offers tools to give a competitive edge in predictive analytics, business intelligence, and performance metrics. Fantasy Football is a popular pastime for a large amount of the world, we gathered data around the past 6 seasons of player performance data to see what our community of data scientists could create.

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Harness the power of AI and ML using Splunk and Amazon SageMaker Canvas

AWS Machine Learning Blog

AWS data engineering pipeline The adaptable approach detailed in this post starts with an automated data engineering pipeline to make data stored in Splunk available to a wide range of personas, including business intelligence (BI) analysts, data scientists, and ML practitioners, through a SQL interface.

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