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MARG ERP
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posted on 16 Nov 2024
I applied via Referral and was interviewed in May 2024. There were 4 interview rounds.
30 aptitude questions in 30 minutes
1 topic was given to discuss
posted on 26 May 2023
I am excited to join your team because of your reputation for innovation and commitment to excellence.
I have researched your company and am impressed by your track record of success.
I am excited about the opportunity to work with a team of talented professionals.
I believe that I can contribute to your company's success and help drive growth.
I am looking for a challenging and rewarding role that will allow me to develop...
posted on 24 May 2024
I applied via Approached by Company and was interviewed in Nov 2023. There was 1 interview round.
posted on 15 Nov 2024
I applied via Naukri.com and was interviewed in May 2024. There was 1 interview round.
posted on 16 Oct 2024
I applied via Walk-in and was interviewed before Oct 2023. There was 1 interview round.
I analyze business processes, gather requirements, and provide data-driven insights to improve efficiency and effectiveness.
Conduct interviews with stakeholders to gather requirements
Analyze data to identify trends and opportunities for improvement
Create reports and presentations to communicate findings
Collaborate with cross-functional teams to implement solutions
My strengths include strong analytical skills, attention to detail, and effective communication.
Strong analytical skills - able to analyze data and identify trends to make informed decisions
Attention to detail - meticulous in reviewing documents and ensuring accuracy
Effective communication - able to clearly convey complex information to stakeholders
posted on 31 Mar 2024
I applied via Company Website and was interviewed in Oct 2023. There was 1 interview round.
I applied via Naukri.com and was interviewed before Jan 2021. There was 1 interview round.
posted on 8 Mar 2021
I applied via Referral and was interviewed in Sep 2020. There was 1 interview round.
posted on 3 Jul 2021
Supervised ML is a type of machine learning where the algorithm is trained on labeled data to make predictions or classifications.
Supervised learning involves a dataset with labeled examples
The algorithm learns from the labeled data to make predictions on new, unlabeled data
Examples include image classification, spam filtering, and predicting housing prices
Common algorithms include decision trees, logistic regression,
based on 2 reviews
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