LogicPlum Data Science Associate Interview Questions and Answers

Q1. What is bias v variance tradeoff
Add your answer
Q2. When should bagging v boosting techniques be used
Add your answer

Q1. Difference between fact and figure.
Ans. 
Fact is a statement that can be proven true or false, while figure is a numerical value or statistic.
• Fact is a statement that can be verified or proven true or false.

• Figure is a numerical value or statistic.

• Facts are objective and can be verified through evidence or research.

• Figures are quantitative data used to represent information.

• Example: 'The sky is blue' is a fact, while 'The average temperature is 25 degrees Cel
Answered by AI
Add your answer
Q2. Explain data modelling
Ans. 
Data modelling is the process of creating a visual representation of data to understand its structure, relationships, and patterns.
• Data modelling involves identifying entities, attributes, and relationships in a dataset.

• It helps in organizing data in a way that is easy to understand and analyze.

• Common data modelling techniques include Entity-Relationship (ER) diagrams and UML diagrams.

• Data modelling is essential for da...read more
Answered by AI
Add your answer

Q1. ML and deep learning questions
Add your answer

Q1. Projects discussion
Add your answer
Q2. Chatgpt architecture
Add your answer

Basic DSA questions will be asked Leetcode Easy to medium

Q1. BERT vs LSTM and their speed
Ans. 
BERT is faster than LSTM due to its transformer architecture and parallel processing capabilities.
• BERT utilizes transformer architecture which allows for parallel processing of words in a sentence, making it faster than LSTM which processes words sequentially.

• BERT has been shown to outperform LSTM in various natural language processing tasks due to its ability to capture long-range dependencies more effectively.

• For exa...read more
Answered by AI
Add your answer
Q2. What is multinomial Naive Bayes theorem
Ans. 
Multinomial Naive Bayes is a classification algorithm based on Bayes' theorem with the assumption of independence between features.
• It is commonly used in text classification tasks, such as spam detection or sentiment analysis.

• It is suitable for features that represent counts or frequencies, like word counts in text data.

• It calculates the probability of each class given the input features and selects the class with the
Answered by AI
Add your answer

(51+52+53+......+100) =

Q1. M.s excel , red hat ,
Add your answer
Q2. Introdution M.s word
Add your answer
Q3. Linux , git , mavel , nexus.
Add your answer
Q4. Sonar cube , aws , super putty.
Add your answer

Q1. What are Large Language Models?
Ans. 
Large Language Models are advanced AI models that can generate human-like text based on input data.
• Large Language Models use deep learning techniques to understand and generate text.

• Examples include GPT-3 (Generative Pre-trained Transformer 3) and BERT (Bidirectional Encoder Representations from Transformers).

• They are trained on vast amounts of text data to improve their language generation capabilities.
Answered by AI
Add your answer
Q2. Do you know about RAGs?
Ans. 
RAGs stands for Red, Amber, Green. It is a project management tool used to visually indicate the status of tasks or projects.
• RAGs is commonly used in project management to quickly communicate the status of tasks or projects.

• Red typically indicates tasks or projects that are behind schedule or at risk.

• Amber signifies tasks or projects that are on track but may require attention.

• Green represents tasks or projects that ar...read more
Answered by AI
Add your answer
Q3. Which is the best clustering algorithm?
Ans. 
There is no one-size-fits-all answer as the best clustering algorithm depends on the specific dataset and goals.
• The best clustering algorithm depends on the dataset characteristics such as size, dimensionality, and noise level.

• K-means is popular for its simplicity and efficiency, but may not perform well on non-linear data.

• DBSCAN is good for clusters of varying shapes and sizes, but may struggle with high-dimensional d...read more
Answered by AI
Add your answer

Good execellnt and well done

Q1. Tell me your self
Add your answer
Q2. Tell me why cogniznt
Add your answer