AI News, The Power of Ensembles in Machine Learning
- On Friday, June 8, 2018
- By Read More
The Power of Ensembles in Machine Learning
Amit and Bargava discusses various strategies to build ensemble models, demonstrating how to combine model outputs from various base models (logistic regression, support vector machines, decision trees, etc.) to create a stronger, better model output.
Using an example they covers bagging, boosting, voting and stacking to explore where ensemble models can consistently produce better results when compared against the best-performing single models.
- On Monday, June 24, 2019
The Power of Ensembles - Machine Learning
Creating better models is a critical component to building a good data science product. It is relatively easy to build a first-cut machine-learning model, but what ...
Bargava Subramanian - Machine Learning: Power of Ensembles
Bargava Subramanian - Machine Learning: Power of Ensembles [EuroPython 2016] [22 July 2016] [Bilbao, Euskadi, Spain] ...
Machine Learning: Python and the Power of Ensembles by Bargava Raman Subramanian
"It is relatively easy to build a first-cut machine learning model. But what does it take to build a reasonably good model, or even a state-of-art model ? Ensemble ...
This video is part of the Udacity course "Machine Learning for Trading". Watch the full course at
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