Hitachi Digital Services Associate Interview Questions and Answers

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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I don’t remember now

Q1. Speak for 3 minutes about any topic you like. How will you phrase a sentence for a given topic?
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Q1. Are you willing to relocate? Are you comfortable table with rotational shifts?
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Technical Discussion

Technical Discussion with Coding Test

Q1. Previous Job Details
Ans. 
I worked as a project manager at a consulting firm, leading teams to deliver strategic solutions for clients across various industries.
• Managed a team of 10 consultants to deliver a market entry strategy for a tech startup.

• Conducted data analysis to identify key trends, resulting in a 20% increase in client revenue.

• Facilitated workshops with clients to align project goals and expectations, enhancing client satisfaction.

• ...read more
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Q2. Salary discussion
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Pair programming with an assignment