Deepen AI Interview Questions and Answers

Q1. Tell me something about your self ?
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Q2. What are your strengths?
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Q3. Why are you interested in this job?
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It was leetcode questions for 60 min for 2 questions.

Q1. Tell me about your self
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Q1. Tell me about your work experience
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Q1. What's your motivation to join this team?
Ans. 
I am motivated to join this team because of the challenging work and the opportunity to learn and grow.
• I am excited about the projects this team is working on and the potential impact they can have.

• I am impressed by the team's expertise and collaborative approach.

• I am looking for a supportive and innovative work environment where I can contribute my skills and knowledge.

• I am eager to learn from my colleagues and develo...read more
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Q2. What are the projects/initiatives you have worked-on in your current role?
Ans. 
I have worked on multiple projects including developing a new e-commerce platform and implementing a machine learning algorithm for fraud detection.
• Developed a new e-commerce platform using React and Node.js

• Implemented a machine learning algorithm for fraud detection using Python and TensorFlow

• Collaborated with cross-functional teams to ensure project success

• Improved website performance by optimizing code and reducing
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Q1. Design VS code(any IDE)
Ans. 
Designing an IDE like VS code requires a deep understanding of software development and user experience.
• Identify the target audience and their needs

• Choose the programming languages and frameworks to support

• Create a user-friendly interface with customizable features

• Implement debugging and testing tools

• Ensure compatibility with different operating systems

• Continuously update and improve the IDE based on user feedback
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Q2. Discuss the architechture, limitations and abilities you would want in your app
Ans. 
The app architecture should be scalable, with a user-friendly interface and secure data storage.
• The app should have a modular architecture to allow for easy scalability and maintenance.

• The user interface should be intuitive and easy to navigate.

• The app should have robust security measures in place to protect user data.

• The app should be able to handle large amounts of data and traffic.

• The app should be compatible with m...read more
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Q3. The objective is not to code, but rather to discuss how would you implement certain features
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Q1. No coding involved but deep JavaScript, CSS, Browser, APIs related questions were asked
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Q2. Need to explain very minute details, explain working and uses
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Q3. What is a CDN? How does the browser work?
Ans. 
CDN stands for Content Delivery Network. Browser works by sending requests to servers and receiving responses.
• CDN is a network of servers that deliver content to users based on their geographic location.

• CDN reduces latency and improves website performance.

• Browser sends HTTP requests to servers and receives responses containing HTML, CSS, JS, and other assets.

• Browser renders the received content and displays it to the u
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Q4. CSS positioning
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Q5. Flexbox, Grid, Browser internals
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Q6. NO DSA question ❌
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You get 60 minutes to code an application in your choice of programming stack. Out of which 45 minutes are set aside for implementation and 15 minutes for problem discussion and conclusion.

Make sure that you think out loud while implementing the solution and not just silently coding.

Q1. Conclude the whole process, discuss salary expectations, perks, benefits, and other policy discussions
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Guestimate question on how a new product can be launch

Q1. Questions on what project you worked on
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Q2. Design 2 factor authentication
Ans. 
Implementing 2 factor authentication for enhanced security
• Require users to enter their password as the first factor

• Send a unique code to the user's registered email or phone as the second factor

• Prompt the user to enter the code to complete the authentication process
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Test duration of 1 hour based on probability and control statements

Q1. Ml algorithms that you have prior knowledge about
Ans. 
I have prior knowledge about various machine learning algorithms.
• Linear Regression

• Logistic Regression

• Decision Trees

• Random Forests

• Support Vector Machines

• Naive Bayes

• K-Nearest Neighbors

• Gradient Boosting

• Neural Networks
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Q2. Data visualization techniques you have studied and used
Ans. 
I have studied and used various data visualization techniques including bar charts, line graphs, scatter plots, and heat maps.
• I have experience creating bar charts to compare data across categories

• I have used line graphs to show trends over time

• I have created scatter plots to identify correlations between variables

• I have used heat maps to visualize data density and identify patterns
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