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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.

I learned in this lecture the Boosting Ensemble method.

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.