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I applied via Recruitment Consultant and was interviewed before Apr 2020. There were 4 interview rounds.
Design a system for the stock market
Define the scope of the system
Identify the data sources and types of data to be collected
Design a database schema to store the data
Develop algorithms for data analysis and prediction
Implement a user interface for traders to access the system
Ensure the system is secure and scalable
Top trending discussions
1st round was Aptitude, which is average difficultly level.
2nd round was Group Discussions, here they only check our communication.
Artificial Intelligence is the simulation of human intelligence processes by machines, especially computer systems.
AI involves machines performing tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and language translation.
Machine learning is a subset of AI that enables machines to learn from data and improve their performance over time.
Examples of AI applic...
Power BI is a business analytics tool by Microsoft that provides interactive visualizations and business intelligence capabilities.
Power BI is a data visualization tool used to create interactive reports and dashboards.
It allows users to connect to various data sources, clean and transform data, and create visually appealing reports.
Power BI offers a wide range of visualization options such as charts, graphs, maps, and...
Data can be loaded in Power BI by connecting to various data sources like Excel, SQL databases, online services, etc.
Connect to data sources by clicking on 'Get Data' in Power BI
Select the desired data source (e.g. Excel, SQL Server, SharePoint, etc.)
Choose the specific data tables or queries to import into Power BI
Transform and clean the data using Power Query Editor if needed
Load the data into Power BI model for visu
Developed a predictive analytics model for predicting customer churn in a telecom company.
Used machine learning algorithms like logistic regression and random forest for analysis.
Performed data preprocessing, feature engineering, and model evaluation.
Achieved an accuracy of 85% in predicting customer churn.
Presented findings and recommendations to the telecom company's management team.
Forecasting problem - Predict daily sku level sales
Bias is error due to overly simplistic assumptions, variance is error due to overly complex models.
Bias is the error introduced by approximating a real-world problem, leading to underfitting.
Variance is the error introduced by modeling the noise in the training data, leading to overfitting.
High bias can cause a model to miss relevant relationships between features and target variable.
High variance can cause a model to ...
Parametric models make strong assumptions about the form of the underlying data distribution, while non-parametric models do not.
Parametric models have a fixed number of parameters, while non-parametric models have a flexible number of parameters.
Parametric models are simpler and easier to interpret, while non-parametric models are more flexible and can capture complex patterns in data.
Examples of parametric models inc...
I applied via LinkedIn and was interviewed in Apr 2024. There were 3 interview rounds.
Aptitude test, basic maths and LR
SQL and Visualisation related
Find max from array in Python without using built-in function.
Iterate through the array and compare each element with a variable storing the current maximum value.
If the element is greater than the current maximum, update the variable.
Return the variable after iterating through the entire array.
I applied via Recruitment Consulltant and was interviewed in Aug 2021. There were 2 interview rounds.
Verbal ability, logical reasoning, finding relationship, problem on train, Problem on distance and time, find compound interest
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