Ensemble Learning | Ensemble Learning In Machine Learning | Machine Learning Tutorial | Simplilearn

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Ensemble Learning is a popular machine learning technique for building models. This video on Ensemble Learning covers the basics of Ensemble Learning Methods. You will learn about the Adaboost and Gradient boosting algorithm. You will get an understanding of the Xgboost technique. The video will make you learn how to create a model using Ensemble Learning. Finally, you will look into the model selection and cross-validation skills.

1. Ensemble Learning
2. Overview
3. Ensemble Learning Methods: Part a
4. Ensemble Learning Methods: Part B
5. Working with Adaboost
6. Adaboost Algorithm and Flowchart
7. Gradient Boosting
8. Xgboost
9. Xgboost Parameters: Part a
10. Xgboost Parameters: Partb
11. Demo: Pima Indians Diabetes
12. Model Selection
13. Common Splitting Strategies
14. Demo: Cross Validation
15. Key Takeaways

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hw to tune hyperparameter that best fits to our model? i got confused how we decide n_estimators to our model?

beautyisinmind
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Absolutely beautiful. I must know however, can this be done using R?

kenroyadams
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Is it possible to build ensemble models without using the decision tree?

raveendiaz
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why does this guy has a robot voice ? or he is robot ?

MrBemnet
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This is so great! Thanks so so much! Can you send the codes to me?

fikrewold
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Wonderful explanation ! Can I pls get the code.

surabhidwivedi
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Outstanding video. Can you post the codes here?

KJAS_JU_IITM