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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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Are you familiar with the teacher of machine learning?

Dataconomy

They assist in data cleaning, feature scaling, and transformation, ensuring that the data is in a suitable format for model training. It provides a higher-level interface and enables the creation of informative and visually appealing statistical graphics.

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Get Maximum Value from Your Visual Data

DataRobot

Submit Data. After Exploratory Data Analysis is completed, you can look at your data. Just like for any other project, DataRobot will generate training pipelines and models with validation and cross-validation scores and rate them based on performance metrics. Configure Settings You Need.

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Top 50+ Data Analyst Interview Questions & Answers

Pickl AI

This comprehensive blog outlines vital aspects of Data Analyst interviews, offering insights into technical, behavioural, and industry-specific questions. It covers essential topics such as SQL queries, data visualization, statistical analysis, machine learning concepts, and data manipulation techniques.

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Build a Stocks Price Prediction App powered by Snowflake, AWS, Python and Streamlit?—?Part 2 of 3

Mlearning.ai

Data storage : Store the data in a Snowflake data warehouse by creating a data pipe between AWS and Snowflake. Data Extraction, Preprocessing & EDA : Extract & Pre-process the data using Python and perform basic Exploratory Data Analysis. The data is in good shape.

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