Remove 2016 Remove Data Analysis Remove Exploratory Data Analysis
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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. By leveraging cross-validation, we ensured the model’s assessment wasn’t reliant on a singular data split.

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The effectiveness of clustering in IIoT

Mlearning.ai

With the emergence of data science and AI, clustering has allowed us to view data sets that are not easily detectable by the human eye. Thus, this type of task is very important for exploratory data analysis. 1207–1221, May 2016, doi: 10.1109/JSAC.2016.2545384. 2016.2545384. BECOME a WRITER at MLearning.ai

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Unveiling Market Dynamics: Winners of the Google Trends Analysis and Predictive Modeling

Ocean Protocol

Participants demonstrated outstanding abilities in utilizing ML and data analysis to probe and predict movements within the cryptocurrency market. His exploratory data analysis (EDA) revealed that Bitcoin showed a 1200% increase in Google search interest from 2016 to 2017, correlating with a price surge from $1,000 to nearly $20,000.

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Multivariate Time Series Forecasting

Mlearning.ai

The Art of Forecasting in the Retail Industry Part I : Exploratory Data Analysis & Time Series Analysis In this article, I will conduct exploratory data analysis and time series analysis using a dataset consisting of product sales in different categories from a store in the US between 2015 and 2018.

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How to tackle lack of data: an overview on transfer learning

Data Science Blog

Presumably due to this fact, Andrew Ng, in his presentation in NeurIPS 2016, gave a rough and abstract predictions of how transfer learning in machine learning would make commercial success like white lines in the figure below. “Shut up and annotate!” ” could be often the best practice in practice.