Remove 2022 Remove Data Visualization Remove Exploratory Data Analysis
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What is Data Pipeline? A Detailed Explanation

Smart Data Collective

The final point to which the data has to be eventually transferred is a destination. The destination is decided by the use case of the data pipeline. It can be used to run analytical tools and power data visualization as well. Otherwise, it can also be moved to a storage centre like a data warehouse or lake.

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Five machine learning types to know

IBM Journey to AI blog

Unsupervised machine learning Unsupervised learning algorithms—like Apriori, Gaussian Mixture Models (GMMs) and principal component analysis (PCA)—draw inferences from unlabeled datasets, facilitating exploratory data analysis and enabling pattern recognition and predictive modeling.

professionals

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

Ocean Protocol

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. This report took the data set provided in the challenge, as well as external data feeds and alternative sources.

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

Mlearning.ai

Figure 4: Google Trends website In this case, we are going to use to search car brand such as Kia, Mitsubishi, Peugeot, Fuso, Chery, MG and GAC Motor in some countries in South America such as Argentina, Bolivia, Chile, Colombia, and Peru, between 01–01–2021 and 31–12–2022. dataframe for kia searches in Peru or MG searches in Colombia).

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Data scientist

Dataconomy

Analyzing data trends: Using analytic tools to identify significant patterns and insights for business improvement. Data visualization: Creating dashboards and visual reports to clearly communicate findings to stakeholders. Machine learning: Developing models that learn and adapt from data.