Live Stream - Target Encoding/AMA/Silly Songs!!! @statquest
Live Stream - Target Encoding/AMA/Silly Songs!!!  @statquest
Uploaded October 2022 | Updated September 2026, 1 week ago
A lot of machine learning algorithms can not deal with categorical data (like "favorite color" or "country code") directly. As a result, we have translate them into some sort of numerical value. The most common practice is to use something called One-Hot-Encoding, which is fine if you don't have many options for each category. However, if you have a lot of options, things get out of hand quickly. This is where methods like Target Encoding really start to shine, so that's what we'll talk about today. We'll also have time for any question you might have for me and maybe even a few silly songs! TRIPLE BAM!!!

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Live Stream - Target Encoding/AMA/Silly Songs!!!Conditional Probabilities, Clearly Explained!!!Decision and Classification Trees, Clearly Explained!!!StatQuest on DeepLearning.AI!!! Check out my short course on attention!The Essence of Linear Regression!!!The Binomial Distribution in 30 Seconds!!!Ken Jees #66DaysOfData Challenge Clearly Explained!!!R-squared, Clearly Explained!!!Decoder-Only Transformers, ChatGPTs specific Transformer, Clearly Explained!!!Live 2020-03-16!!! Naive BayesPCA EigenvectorsThe Cosine Similarity for NLP and CatBoost
StatQuest with Josh Starmer |

Live Stream - Target Encoding/AMA/Silly Songs!!!

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