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I appeared for an interview in Apr 2020.
I have 3 years of experience working as a data analyst at a tech company.
Analyzed large datasets to extract valuable insights
Created data visualizations to communicate findings to stakeholders
Collaborated with cross-functional teams to improve data quality and accuracy
I appeared for an interview in Mar 2020.
I appeared for an interview before Oct 2019.
I applied via Referral and was interviewed in May 2022. There were 3 interview rounds.
I applied via Company Website and was interviewed in Jun 2023. There were 2 interview rounds.
I was asked to solve various problems (your typical algorithm and data structure subjects), as well as explain the various projects I worked on in my most recent position.
Divide candidates in a group of around 15 people, and put you through different activities such as role play exercises to measure your communication and team working skills.
I expect challenging projects, opportunities for growth, collaborative team environment, and work-life balance.
Challenging projects that allow me to apply my data science skills and learn new techniques
Opportunities for growth and advancement within the company
Collaborative team environment where I can share ideas and work together towards common goals
Work-life balance to ensure I can perform at my best both profession
Topic was joining and calculating
XGBoost is a popular machine learning algorithm known for its speed and performance in gradient boosting.
XGBoost stands for eXtreme Gradient Boosting.
It is an implementation of gradient boosted decision trees designed for speed and performance.
XGBoost is widely used in machine learning competitions and has become a popular choice for data scientists.
It can handle missing data and is optimized for parallel processing.
XG...
Decision tree is a predictive modeling tool that uses a tree-like graph of decisions and their possible consequences.
Decision tree is a supervised learning algorithm used for classification and regression tasks.
It breaks down a dataset into smaller subsets based on different attributes.
Each internal node represents a feature or attribute, each branch represents a decision rule, and each leaf node represents the outcome...
I appeared for an interview before Feb 2023.
ACF measures the linear relationship between an observation and its lagged values. PACF measures the direct relationship.
ACF (Autocorrelation Function) measures the correlation between an observation and its lagged values.
PACF (Partial Autocorrelation Function) measures the correlation between an observation and its lagged values, while removing the indirect effects of intermediate lags.
ACF is used to identify the orde...
posted on 2 Jan 2025
Basic python questions
I applied via Referral and was interviewed in Nov 2023. There were 2 interview rounds.
Ml algorithms ,deeplearning, nlp questioons and projects
Python basic codeing
based on 1 review
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