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I applied via Approached by Company and was interviewed in Apr 2024. There was 1 interview round.
I applied via Recruitment Consulltant and was interviewed before Apr 2023. There were 4 interview rounds.
Gradient Boost is a machine learning technique that builds models in a sequential manner, where each new model corrects errors made by the previous one.
Gradient Boost combines multiple weak learners to create a strong learner.
It focuses on reducing the errors made by the previous models by giving more weight to the misclassified data points.
Popular implementations include XGBoost, LightGBM, and CatBoost.
Gradient Boost ...
Evaluation metric selection is crucial for assessing the performance of a machine learning model.
Consider the specific problem domain and objectives of the model
Choose metrics that align with the business goals
Select metrics that are easy to interpret and communicate
Balance between different metrics to get a comprehensive view of model performance
Examples of evaluation metrics include accuracy, precision, recall, F1 sc
I applied via Approached by Company and was interviewed before Jun 2022. There were 3 interview rounds.
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I applied via Referral and was interviewed before May 2021. There was 1 interview round.
I applied via Referral and was interviewed before Nov 2019. There were 3 interview rounds.
I applied via Naukri.com and was interviewed in Jan 2021. There were 5 interview rounds.
I applied via Naukri.com and was interviewed before Jul 2021. There was 1 interview round.
I applied via Naukri.com and was interviewed before Jun 2021. There were 3 interview rounds.
I applied via Approached by Company and was interviewed before Dec 2022. There were 3 interview rounds.
I applied via Naukri.com and was interviewed before Jun 2022. There were 3 interview rounds.
A random topic was given to each participant. The participant have 2 minutes to think about the topic and 3 minutes to share his/her thoughts/views about the topic.
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Mumbai,
Gurgaon / Gurugram
+110-15 Yrs
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Bangalore / Bengaluru
3-7 Yrs
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