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I appeared for an interview before Jul 2021.
Bagging and boosting are ensemble techniques used to improve the accuracy of machine learning models.
Bagging involves training multiple models on different subsets of the training data and then combining their predictions through voting or averaging.
Boosting involves iteratively training models on the same data, with each subsequent model focusing on the samples that the previous models misclassified.
Bagging reduces va...
I applied via Recruitment Consultant and was interviewed in Sep 2020. There were 3 interview rounds.
posted on 29 Mar 2022
I applied via Naukri.com and was interviewed in Mar 2022. There were 2 interview rounds.
NER training using deep learning
I approach assignments by breaking them down into smaller tasks, setting deadlines, and regularly checking progress.
Break down the assignment into smaller tasks to make it more manageable
Set deadlines for each task to stay on track
Regularly check progress to ensure everything is on schedule
Seek feedback from colleagues or supervisors to improve the quality of work
I applied via Referral and was interviewed before Aug 2022. There were 4 interview rounds.
Fundamentals of classical machine learning
Classical machine learning involves algorithms that learn from data and make predictions or decisions.
Common algorithms include linear regression, decision trees, support vector machines, and k-nearest neighbors.
Key concepts include training data, testing data, model evaluation, and hyperparameter tuning.
Classical ML is often used for tasks like classification, regression, clus
I applied via Recruitment Consultant and was interviewed in Mar 2021. There were 3 interview rounds.
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