ITC
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I was interviewed before Dec 2023.
Every participant was allowed to speak in sequential matter on a given ethics based imaginary scenario.
Missing data can be handled by imputation, deletion, or using algorithms that can handle missing values.
Imputation: Fill missing values with mean, median, mode, or using predictive modeling.
Deletion: Remove rows or columns with missing values.
Algorithms: Use algorithms like Random Forest, XGBoost, or LightGBM that can handle missing values.
Consider the reason for missing data and choose the appropriate method for handl
Random Forest Classifier is an ensemble learning method that builds multiple decision trees and merges them to improve accuracy.
Random Forest is a collection of decision trees that work together to make predictions.
Each tree in the Random Forest is built using a subset of the training data and a random subset of features.
The final prediction is made by aggregating the predictions of all the individual trees, usually th...
Choose the project based on alignment with organizational goals, available resources, and potential impact.
Consider the alignment of the project with the organization's goals and objectives.
Evaluate the available resources such as data, expertise, and time for each project.
Assess the potential impact of each project on the organization's success and growth.
Prioritize projects that have clear deliverables, measurable ou...
I would try to understand the reasons behind the opposition and work towards finding a solution that addresses concerns.
Initiate a discussion with the manager to understand their concerns and reasons for opposition
Present a detailed analysis of the project, highlighting its potential benefits and addressing any potential risks or drawbacks
Propose alternative solutions or adjustments to the project plan that may allevia...
posted on 17 Oct 2023
I applied via Company Website and was interviewed in Apr 2023. There were 3 interview rounds.
Written test testing logical abilities
posted on 15 Oct 2024
Handling large volumes of data, ensuring data quality, and interpreting complex data.
Dealing with unstructured data from various sources
Ensuring data quality and accuracy through data cleaning and preprocessing
Interpreting complex data and deriving meaningful insights
Implementing machine learning algorithms to analyze data
Communicating findings to non-technical stakeholders
It has behavioural and ability to focus rounds where behavioural have several questions repeated in different forms and answers in different categories. Choose extreme ones, it shows your confidence and clarify
Calculate impact of a project by analyzing key metrics and outcomes.
Identify key metrics to measure impact such as revenue, cost savings, customer satisfaction, etc.
Quantify the baseline performance before the project and compare it to the performance after the project.
Use statistical analysis to determine the significance of the project's impact.
Consider both short-term and long-term effects of the project.
Seek feedba...
I applied via LinkedIn and was interviewed in Sep 2023. There were 2 interview rounds.
Some standard test and aptitude test everyone has to take before being shortlisted for itnerview
GitHub commands are used to interact with repositories on GitHub platform.
git clone
git add
git commit -m 'commit message': Commit changes to the repository
git push origin
git pull origin
posted on 21 Jun 2024
I applied via Approached by Company and was interviewed before Jun 2023. There were 4 interview rounds.
Forecasting of products demands
posted on 17 Oct 2023
I applied via Company Website and was interviewed in Apr 2023. There were 3 interview rounds.
Written test testing logical abilities
I applied via Referral and was interviewed before Jun 2023. There were 4 interview rounds.
Data Science MCQ questions
Building a baseline ML model with EDA etc.
Outliers can be analyzed using statistical methods like Z-score, IQR, or visualization techniques like box plots.
Calculate Z-score and identify data points with Z-score greater than a certain threshold as outliers.
Use Interquartile Range (IQR) to detect outliers by identifying data points outside 1.5 * IQR range.
Visualize data using box plots to identify any data points that fall outside the whiskers.
Consider domain kn...
based on 1 review
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