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XGBoost Part 1 (of 4): Regression
25:46
YouTubeStatQuest with Josh Starmer
XGBoost Part 1 (of 4): Regression
XGBoost is an extreme machine learning algorithm, and that means it's got lots of parts. In this video, we focus on the unique regression trees that XGBoost uses when applied to Regression problems. NOTE: This StatQuest assumes that you are already familiar with... The main ideas behind Gradient Boost for ...
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XGBoost Machine Learning
Interviewer: Why XGBoost is better than normal Gradient Boosting? Ans: because it uses Hessians!
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yourquant_rick on Instagram: "Time series models, like ARIMA, are a classic framework for analyzing sequential data. They assume stationarity and lack of correlation, which works well for sales forecasting but struggles in finance. Markets are highly non-stationary — factors like inflation, rising costs, and constant shifts in sentiment affect price behavior. Correlation between assets is often temporary and only strong in high-sentiment markets like crypto or tech. I often combine uncorrelated
yourquant_rick on Instagram: "Time series models, like ARIMA, are a classic framework for analyzing sequential data. They assume stationarity and lack of correlation, which works well for sales forecasting but struggles in finance. Markets are highly non-stationary — factors like inflation, rising costs, and constant shifts in sentiment affect price behavior. Correlation between assets is often temporary and only strong in high-sentiment markets like crypto or tech. I often combine uncorrelated
Instagramyourquant_rick
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