ArisGlobal Associate Lead Interview Questions and Answers

Q1. General Java, springboot and oops
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Q1. Managerial round with Technical Lld and design related questions
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Q1. Client round technical LLD AND HLD questions
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Q1. HR discussion about salary and client details
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Q1. Explain random forest
Ans. 
Random forest is an ensemble learning method that builds multiple decision trees and merges them to improve accuracy and prevent overfitting.
• Random forest is a type of ensemble learning method.

• It builds multiple decision trees during training.

• Each tree is built using a subset of the training data and a random subset of features.

• The final prediction is made by averaging the predictions of all the individual trees.

• Random...read more
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Q2. What is boosting
Ans. 
Boosting is a machine learning ensemble technique where multiple weak learners are combined to create a strong learner.
• Boosting is an iterative process where each weak learner is trained based on the errors of the previous learners.

• Examples of boosting algorithms include AdaBoost, Gradient Boosting, and XGBoost.

• Boosting is used to improve the accuracy of models and reduce bias and variance.
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Q1. What are the strengths and weakness
Ans. 
Strengths include strong analytical skills and attention to detail. Weaknesses may include difficulty with public speaking and time management.
• Strengths: strong analytical skills

• Strengths: attention to detail

• Weaknesses: difficulty with public speaking

• Weaknesses: time management
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Basic coding question and JavaScript in depth questions

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