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Agileengine Interview Questions and Answers
Ques:- Why do we have two types of scheduling options in Primavera – Retained logic and progress override? What is the difference between the two and when is either one selected?
Right Answer:
In Primavera, we have two types of scheduling options: Retained Logic and Progress Override.

- **Retained Logic** maintains the original relationships and dependencies between tasks, ensuring that the schedule reflects the planned sequence of work. It is selected when you want to keep the integrity of the project plan intact.

- **Progress Override** allows for adjustments to the schedule based on actual progress, which can change the relationships between tasks. It is selected when you need to reflect real-time updates and changes in task completion that may affect the overall schedule.

Use Retained Logic for accurate planning and Progress Override for flexibility in managing ongoing project changes.
Ques:- What is clustering in data analysis and how is it different from classification
Right Answer:
Clustering in data analysis is the process of grouping similar data points together based on their characteristics, without prior labels. It is an unsupervised learning technique. In contrast, classification involves assigning predefined labels to data points based on their features, using a supervised learning approach.
Ques:- What is the purpose of feature engineering in data analysis
Right Answer:
The purpose of feature engineering in data analysis is to create, modify, or select variables (features) that improve the performance of machine learning models by making the data more relevant and informative for the analysis.
Ques:- What is exploratory data analysis (EDA)
Right Answer:
Exploratory Data Analysis (EDA) is the process of analyzing and summarizing datasets to understand their main characteristics, often using visual methods. It helps identify patterns, trends, and anomalies in the data before applying formal modeling techniques.
Ques:- What is the difference between supervised and unsupervised learning
Right Answer:
Supervised learning uses labeled data to train models, meaning the output is known, while unsupervised learning uses unlabeled data, where the model tries to find patterns or groupings without predefined outcomes.
Ques:- What are the different types of data distributions
Right Answer:
The different types of data distributions include:

1. Normal Distribution
2. Binomial Distribution
3. Poisson Distribution
4. Uniform Distribution
5. Exponential Distribution
6. Log-Normal Distribution
7. Geometric Distribution
8. Beta Distribution
9. Chi-Squared Distribution
10. Student's t-Distribution
Ques:- What is Git and why is it used
Right Answer:

Git is a distributed version control system used to track changes in source code during software development. It allows multiple developers to collaborate, manage code versions, and maintain a history of changes efficiently.

Ques:- What is the difference between merge and rebase?
Right Answer:

Merge combines two branches by creating a new commit that includes changes from both, preserving the history of both branches. Rebase, on the other hand, moves or combines a sequence of commits to a new base commit, creating a linear history without a merge commit.

Ques:- What is the difference between git add, git commit, and git push?
Right Answer:

– **git add**: Stages changes in your working directory for the next commit.
– **git commit**: Records the staged changes in the repository's history with a message.
– **git push**: Uploads your local commits to a remote repository.

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