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Hyperparameters are settings that control the behavior of machine learning algorithms.
Hyperparameters are set before training the model.
They control the learning process and affect the model's performance.
Examples include learning rate, regularization strength, and number of hidden layers.
Optimizing hyperparameters is important for achieving better model accuracy.
Hyperparameters of XGBoost, Random Forest, and SVM can be tuned using techniques like grid search, random search, and Bayesian optimization.
For XGBoost, important hyperparameters to tune include learning rate, maximum depth, and number of estimators.
For Random Forest, important hyperparameters to tune include number of trees, maximum depth, and minimum samples split.
For SVM, important hyperparameters to tune inclu...
Answering a question on data and objective function for cost and revenue optimization case studies.
For cost optimization, look at data related to expenses, production costs, and resource allocation.
For revenue optimization, look at data related to sales, customer behavior, and market trends.
Objective function for cost optimization could be minimizing expenses while maintaining quality.
Objective function for revenu...
Time series modeling involves analyzing data points collected or recorded at specific time intervals to forecast future values.
Identify the type of time series data: univariate (single variable) or multivariate (multiple variables).
Visualize the data using plots to identify trends, seasonality, and anomalies.
Decompose the time series into trend, seasonality, and residual components for better understanding.
Use mod...
Oracle and SQL error logs are crucial for diagnosing database issues and performance monitoring.
Oracle alert log: Located in the 'alert_' directory, typically found in the 'diag' directory of the Oracle home.
SQL Server error log: Found in the SQL Server Management Studio under 'Management' > 'SQL Server Logs'.
Example of Oracle alert log entry: 'ORA-01555: snapshot too old' indicates a problem with undo data.
Exa...
SQL backup details involve methods, types, and best practices for securing database data.
Types of backups: Full, Differential, and Transaction Log backups.
Full backup captures the entire database; e.g., 'BACKUP DATABASE myDB TO DISK = 'C:\myDB.bak';'
Differential backup saves changes since the last full backup; e.g., 'BACKUP DATABASE myDB TO DISK = 'C:\myDB_diff.bak' WITH DIFFERENTIAL;'
Transaction Log backup record...
An unique id for a massive parallel system can be generated using a combination of timestamp, machine id and a random number.
Use a timestamp to ensure uniqueness
Include a machine id to avoid collisions in a distributed system
Add a random number to further increase uniqueness
Consider using a UUID (Universally Unique Identifier) for simplicity
Ensure the id generation algorithm is thread-safe
A parking lot system that manages parking spots and vehicles.
Create a class for parking lot with attributes like total number of spots, available spots, etc.
Create a class for vehicle with attributes like license plate number, type, etc.
Implement methods for parking a vehicle, removing a vehicle, and checking availability of spots.
Use data structures like arrays and maps to store and retrieve information.
Consider ...
Five useful Excel shortcuts for efficient data analysis.
Ctrl + C: Copy selected cells
Ctrl + V: Paste copied cells
Ctrl + Z: Undo previous action
Ctrl + Shift + Arrow Key: Select entire data range in a direction
Ctrl + Home: Move to cell A1
Standard ADSO is for persistent storage and reporting, while write optimized DSO is for temporary storage. Keys in ADSO are used for data modeling and performance optimization.
Standard ADSO is used for persistent storage and reporting, while write optimized DSO is used for temporary storage before loading data to a standard ADSO.
Write optimized DSO does not store data persistently, making it suitable for temporary...
I applied via Recruitment Consulltant and was interviewed in Nov 2024. There was 1 interview round.
Catalog Analyst role involves managing product data, ensuring accuracy and consistency in catalogs.
Responsible for creating, updating, and maintaining product catalogs
Ensuring accuracy and consistency of product data
Analyzing catalog performance and making recommendations for improvements
Collaborating with cross-functional teams such as marketing, sales, and product development
Knowledge of data management systems and t...
Five useful Excel shortcuts for efficient data analysis.
Ctrl + C: Copy selected cells
Ctrl + V: Paste copied cells
Ctrl + Z: Undo previous action
Ctrl + Shift + Arrow Key: Select entire data range in a direction
Ctrl + Home: Move to cell A1
Pivot table for summarizing data, vlookup for finding values in a table, hlookup for horizontal lookup, xlookup for advanced lookup.
Pivot table is used to summarize and analyze large datasets.
VLOOKUP is used to find a value in a table by row.
HLOOKUP is used to find a value in a table by column.
XLOOKUP is a more advanced version of VLOOKUP and HLOOKUP, allowing for more flexibility in searching for data.
Example: Use piv...
I applied via Naukri.com and was interviewed in Jul 2024. There were 3 interview rounds.
Calculate the amount of water that can be trapped between bars after rainfall using heights of bars.
Use two pointers to traverse the array from both ends towards the center.
Maintain two variables to track the maximum height from the left and right.
At each step, calculate trapped water based on the minimum of the two maximum heights.
Example: For heights [0,1,0,2,1,0,1,3,2,1,2,1], the trapped water is 6.
I appeared for an interview before Jul 2024, where I was asked the following questions.
I have over 7 years of experience in data analysis, focusing on financial modeling and market research to drive strategic decisions.
Led a team of analysts in developing financial models that improved forecasting accuracy by 20%.
Conducted market research that identified new growth opportunities, resulting in a 15% increase in revenue.
Utilized advanced statistical techniques to analyze large datasets, enhancing decision-...
I have extensive experience in team management, focusing on collaboration, conflict resolution, and performance optimization.
Led a cross-functional team of 10 in a project that improved operational efficiency by 20%.
Implemented regular feedback sessions to enhance team communication and address concerns promptly.
Facilitated team-building activities that fostered trust and collaboration, resulting in a 15% increase in p...
I applied via Job Portal and was interviewed in Oct 2024. There was 1 interview round.
Cost optimization in Big Query involves optimizing query performance, storage usage, and data transfer costs.
Utilize partitioned tables to reduce query costs by scanning only relevant partitions
Use clustering to organize data within partitions and improve query performance
Optimize queries by using efficient SQL syntax and avoiding unnecessary operations
Leverage caching to reduce repeated query costs
Monitor and analyze ...
Various ways to ingest data in BigQuery include batch loading, streaming, and using third-party tools.
Batch loading: Uploading data in bulk using tools like Cloud Storage or Data Transfer Service.
Streaming: Sending data in real-time using APIs like Dataflow or Pub/Sub.
Third-party tools: Using tools like Talend or Informatica for data ingestion.
I appeared for an interview in May 2025, where I was asked the following questions.
I'm seeking new challenges and opportunities for growth that align with my career goals and aspirations.
Desire for professional growth: I'm looking for a role that offers more opportunities for advancement.
Seeking new challenges: My current position has become routine, and I'm eager to tackle new problems.
Alignment with career goals: I want to work in a company that shares my values and vision for the future.
Desire to ...
I applied via Approached by Company and was interviewed in Mar 2024. There were 5 interview rounds.
I appeared for an interview in Mar 2025, where I was asked the following questions.
Converting SQL queries to PySpark involves translating SQL syntax into DataFrame operations.
Use `spark.sql()` for executing SQL queries directly on DataFrames.
For SELECT statements, use `df.select('column_name')`.
For WHERE clauses, use `df.filter('condition')`.
JOIN operations can be performed using `df1.join(df2, 'key')`.
GROUP BY can be achieved with `df.groupBy('column_name').agg({'agg_column': 'agg_function'})`.
I applied via Newspaper Ad and was interviewed in Jul 2024. There were 3 interview rounds.
Dynamic team leader with a proven track record in project management, team development, and strategic planning.
Over 5 years of experience leading diverse teams in high-pressure environments.
Successfully managed a project that increased efficiency by 30% through process optimization.
Skilled in conflict resolution, having mediated disputes that resulted in improved team cohesion.
Implemented training programs that enhance...
My strength lies in effective communication and team collaboration, fostering a positive work environment and driving project success.
Strong interpersonal skills: I actively listen to team members, ensuring everyone feels heard and valued.
Conflict resolution: I mediate disputes by encouraging open dialogue, leading to quicker resolutions and a harmonious team dynamic.
Goal-oriented leadership: I set clear objectives and...
General topic and current affairs and company topic
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Some of the top questions asked at the Walmart interview for experienced candidates -
The duration of Walmart interview process can vary, but typically it takes about less than 2 weeks to complete.
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