Remove Clean Data Remove Cross Validation Remove Data Visualization
article thumbnail

Predict football punt and kickoff return yards with fat-tailed distribution using GluonTS

Flipboard

Models were trained and cross-validated on the 2018, 2019, and 2020 seasons and tested on the 2021 season. To avoid leakage during cross-validation, we grouped all plays from the same game into the same fold. For more information on how to use GluonTS SBP, see the following demo notebook.

article thumbnail

Cheat Sheets for Data Scientists – A Comprehensive Guide

Pickl AI

Here, we’ll explore why Data Science is indispensable in today’s world. Understanding Data Science At its core, Data Science is all about transforming raw data into actionable information. It includes data collection, data cleaning, data analysis, and interpretation.

article thumbnail

[Updated] 100+ Top Data Science Interview Questions

Mlearning.ai

The following figure represents the life cycle of data science. It starts with gathering the business requirements and relevant data. Once the data is acquired, it is maintained by performing data cleaning, data warehousing, data staging, and data architecture. What is Cross-Validation?