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Completing Data Science Tasks in Seconds, Not Minutes

Smart Data Collective

When it comes to data analytics , not much is easier to use than a spreadsheet. For this reason, spreadsheets have been the predominant tool when it comes to basic data analysis for the past 20 years. If you work with data, you’ve done work in Excel or Google Sheets. Easy Smeasy. Easy, Powerful, and Flexible.

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Exploring Different Types of Data Analysis: Methods and Applications

Pickl AI

Summary: This article explores different types of Data Analysis, including descriptive, exploratory, inferential, predictive, diagnostic, and prescriptive analysis. Introduction Data Analysis transforms raw data into valuable insights that drive informed decisions. What is Data Analysis?

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From Data to Decisions: Deep Dive into Workshop Learnings

Women in Big Data

Learning Objectives Recap: Paradigms in Data Science: We explored the two main paradigms in data science: descriptive analytics (understanding what happened in the past) and predictive analytics (using models to forecast future outcomes).

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

Data Science Blog

And importantly, starting naively annotating data might become a quick solution rather than thinking about how to make uses of limited labels if extracting data itself is easy and does not cost so much. In that case, you tasks have your own problem, and you would have to be careful about your EDA, data cleaning, and labeling.

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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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Curve Finance Data Challenge Review & Insights Research

Ocean Protocol

Abstract This research report encapsulates the findings from the Curve Finance Data Challenge , a competition that engaged 34 participants in a comprehensive analysis of the decentralized finance protocol. Part 1: Exploratory Data Analysis (EDA) MEV Over 25,000 MEV-related transactions have been executed through Curve.

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AI in Time Series Forecasting

Pickl AI

Summary: AI in Time Series Forecasting revolutionizes predictive analytics by leveraging advanced algorithms to identify patterns and trends in temporal data. This is due to the growing adoption of AI technologies for predictive analytics. Making Data Stationary: Many forecasting models assume stationarity.

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