Avieum Life Sciences Interview Questions and Answers

Q1. Describe projects?
Ans. 
I have worked on various projects ranging from data analysis to machine learning models.
• Developed a sentiment analysis model using natural language processing techniques

• Implemented a recommendation system based on collaborative filtering algorithm

• Worked on a predictive maintenance project for optimizing equipment performance
Answered by AI
Add your answer
Q2. Explain architecture of Efficient-nets
Ans. 
EfficientNets are a family of convolutional neural networks that have been designed to achieve state-of-the-art accuracy with fewer parameters and FLOPS.
• EfficientNets use a compound scaling method to balance network depth, width, and resolution for optimal performance.

• They are based on a baseline network architecture called EfficientNet-B0, which is then scaled up to create larger models like EfficientNet-B1, Efficient...read more
Answered by AI
Add your answer
Q3. Explain transformers architecture
Ans. 
Transformers architecture is a deep learning model that uses self-attention mechanism to process sequential data.
• Transformers consist of an encoder and a decoder, each composed of multiple layers of self-attention and feed-forward neural networks.

• Self-attention mechanism allows the model to weigh the importance of different input tokens when making predictions.

• Transformers have achieved state-of-the-art performance in ...read more
Answered by AI
Add your answer
Q4. Longest sub array question in python.
Ans. 
Find the longest subarray of strings in a given array.
• Iterate through the array and keep track of the current subarray length.

• Reset the subarray length when encountering a non-string element.

• Return the length of the longest subarray found.
Answered by AI
Add your answer

Q1. About family and past life
Add your answer
Q2. Past internships and learnings
Add your answer
Q3. College life and what they expect.
Add your answer

Q1. Tell us about yourself
Add your answer
Q2. Showcase some of you projects
Ans. 
I have worked on projects involving website redesign, mobile app design, and user research.
• Redesigned company website to improve user experience and increase conversion rates

• Designed mobile app interface for seamless navigation and intuitive user interactions

• Conducted user research to gather feedback and make data-driven design decisions
Answered by AI
Add your answer
Q3. What are your favourite apps and why do you like them
Ans. 
My favorite apps are Instagram for its user-friendly interface and engaging content, Spotify for its personalized music recommendations, and Google Maps for its accurate navigation features.
• Instagram - user-friendly interface, engaging content

• Spotify - personalized music recommendations

• Google Maps - accurate navigation features
Answered by AI
Add your answer
Q4. What roles are you interested in?
Add your answer
Q5. Where do you see yourself in 5 years?
Ans. 
In 5 years, I see myself as a seasoned UI/UX designer leading a team of designers, working on innovative projects, and continuously learning and growing in the field.
• Leading a team of designers

• Working on innovative projects

• Continuously learning and growing in the field
Answered by AI
Add your answer

A random topic was given and we had to speak on it

Q1. Why do u want to join us
Ans. 
I am passionate about data science and believe your company offers a great opportunity for growth and learning.
• Passionate about data science

• Believe company offers growth and learning opportunities
Answered by AI
Add your answer
Q2. A guestimate question, how many tea cups are consumed daily in delhi
Add your answer

Q1. What is Bias In ML?
Ans. 
Bias in ML refers to the systematic error in a model's predictions, leading to inaccurate results.
• Bias is the algorithm's tendency to consistently learn the wrong thing by not taking all factors into account.

• It can result from the data used to train the model being unrepresentative or skewed.

• Bias can lead to unfair or discriminatory outcomes, especially in sensitive areas like hiring or lending decisions.

• Examples inclu...read more
Answered by AI
Add your answer
Q2. Regression concept in ML
Ans. 
Regression in ML is a supervised learning technique used to predict continuous values based on input features.
• Regression models establish a relationship between dependent and independent variables.

• Common regression algorithms include linear regression, polynomial regression, and logistic regression.

• Evaluation metrics for regression models include Mean Squared Error (MSE) and R-squared.

• Example: Predicting house prices b...read more
Answered by AI
Add your answer

50 question in 15 mins

Q1. On site evaluation, where various tasks were given
Add your answer
Q2. Why do u want to join us
Ans. 
I am passionate about data science and believe your company offers a great opportunity for growth and learning.
• I am passionate about data science and enjoy working with data to derive insights and make informed decisions.

• I believe your company is at the forefront of innovation in the field of data science, and I am excited about the opportunity to learn from experts in the industry.

• I am impressed by the projects your c...read more
Answered by AI
Add your answer