Reducing the size of your data can sometimes be tricky. In this quick tutorial, we will demonstrate how to reduce the size of your dataframe in half by down casting allowing you to do more with less.

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Background

Understanding the size of our data


An extensive guide to structuring data to predict future sales using machine learning. It walks through how to use python to create lagged variables, rolling means and time-based features. It covers how to perform target encoding, train test splitting for time dependent models and build a gradient boosted tree model predicting next month’s sales for a retailer.

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The Problem Statement


These books will help you grow the skills needed to prepare you for a data analytics leadership role.

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An introduction to building trust in machine learning through global and local variable importance using post-hoc explanations

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How to structure customer churn problems with classification and survival analysis

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Nicklas Ankarstad

Analytics leader with experience in data warehousing, data science and business intelligence.

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