Time Series Clustering - Mixture Models for Clustering
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Time Series Clustering - Mixture Models for Clustering
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Time Series Clustering - Mixture Models for Clustering
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This is difficult enough, but even once a vision is in place, many leaders fail to execute it over the many years that it may require. They don’t translate the vision into a structured plan that they keep in focus over time. When change efforts require years, however, tracking often gets fuzzy, falling away in the face of rapidly changing business and economic conditions that force constant adaptation to produce day-to-day results.
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XGBoost with monotonic constraints gives 7% higher KS compared to traditional score-card model and explainability problem is being solved using SHAP explanations.
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Interpretability versus performance trade-off given common ML algorithms. Source — http://tinyurl.com/4n5xtszb
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1979 Iranian Revolution:
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Noble Prize Chemistry:2024
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Osho vs Krishnamurthy
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The history of the product owner role
• The differences between product owners and product managers
• How to transition from product owner to product manager
• The evolution of and problems with the SAFe framework
• How large non-tech companies can improve their product practices
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