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https://www.kaggle.com/muhammadrameez242 , ye meri kaggle ki I'd hai yha par Ap mukamal assignments simple roman urdu mein mill jai gi codes mein
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In this lecture, I learned about the goal of boosting, how does boosting work?, the advantages of boosting, application of boosting, method or types of boosting.
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I learned in this lecture the Boosting Ensemble method.
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AOA, I learned in this lecture about boosting algorithms from Ensemble family and how they work.1-Initialize weights: At the start of the process, each training example is given an equal weight.
2-Train a weak learner: makes a weak learner strong
3-Error calculation: The error of the weak learner on the training data is computed.
4-Update weights: Weight are updated according to the mistakes
5-Repeat: steps 2-4 are repeated several times.
6-Combine weak learners: The final prediction is based on the weighted total of the weak learners.
7-Forcast:And also learned advantages of boosting, which are1-Improve Performance: (reduces bias and variance, results in more accurate and robust predictions)
2-Ability to Handle Complex Data:( (handling complicated data like non-linear correlation and interaction)
3-Robustness to Noise: (handling outliers effectively )
4-Flexibitily: ( allowing for customization and adaptation to various problem domains)
5-Interpretablity:And I also learned about applications of Boosting algorithms which are1-Classification problems: (spam detection, fraud detection, and disease diagnosis)
2-Regression problems: (housing price prediction and stock market trends)
3-Natural language processing (NLP) task: (sentiment analysis and text classification)
4-Image and speech recognition:
5-Recommendation Systems: (product recommendations and movie recommendations)
6-Time series analysis:
ALLAH PAK aap ko sahat o aafiat wali lambi umar ata kray aor ap ko dono jahan ki bhalian naseeb farmaey or ap k walid-e-mohtram ko karwat karwat jannat ata farmay,Ameen.
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