Wipro Analytics Executive Interview Questions and Answers

Q1. Tell me about yourself?
Ans. 
I am a data scientist with a background in statistics and machine learning, passionate about solving complex problems using data-driven approaches.
• Background in statistics and machine learning

• Experience in solving complex problems using data-driven approaches

• Passionate about leveraging data to drive insights and decision-making
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Q2. Describe in detail about one of my main project.
Ans. 
Developed a predictive model for customer churn in a telecom company.
• Collected and cleaned customer data including usage patterns and demographics.

• Used machine learning algorithms such as logistic regression and random forest to build the model.

• Evaluated model performance using metrics like accuracy, precision, and recall.

• Implemented the model into the company's CRM system for real-time predictions.
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Q3. Few questions related to my projects.
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Q1. Questions on Basics python(Since i am fresher)
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Q1. About Machine learning basics, activation functions linear regression, cnn, all basics..
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Q2. About project questions, about sdlc basic 3 questions
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Q3. About Why not used another model for training?
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Q1. Tell me about your self?
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Q2. What is maths and stats
Ans. 
Maths and stats refer to the study of mathematical concepts and statistical methods for analyzing data.
• Maths involves the study of numbers, quantities, shapes, and patterns.

• Stats involves collecting, analyzing, interpreting, and presenting data.

• Maths is used to solve equations, calculate probabilities, and model real-world phenomena.

• Stats is used to make informed decisions, draw conclusions, and test hypotheses.

• Both ma...read more
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Confusion matrix what are your job rolls explain me Gradient boosting algorithm?

Q1. Difference between supervised and unsupervised learning
Ans. 
Supervised learning uses labeled data to train a model, while unsupervised learning uses unlabeled data.
• Supervised learning requires a target variable for training the model.

• Examples of supervised learning include classification and regression.

• Unsupervised learning finds patterns and relationships in data without a target variable.

• Examples of unsupervised learning include clustering and dimensionality reduction.
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Q2. What is sigmoid function
Ans. 
Sigmoid function is a mathematical function that maps any real value to a value between 0 and 1.
• Used in machine learning for binary classification problems to produce probabilities

• Commonly used in logistic regression

• Has an S-shaped curve

• Equation: f(x) = 1 / (1 + e^(-x))
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A="bala",b="Babu";
Print=A+b
O/p:
balababu

Python is a computer programming language use to build up software and websites designed by Rossum appear in 20 Feb 1991
1.Numpy is a python libraries working with arrays.
2.pandas is used to read the data sets.
3.matplotlib libraries for visualisation.
4.mission learning is divided into two parts.
*Supervised learning
*Unsupervised learning
5.deep learning is used to create artificial neurons.
6.advance excel is used for graphs and calculate the whole members at same time lot of useful things that have.
7mysql is mainly used for store the data.

Python, numpy, pandas, mission learning, deep learning, basic statistics, advance excel, MySQL

Python, numpy, pandas, mission learning, deep learning, basic statistics, advance excel, MySQL

Q1. Why we use mission learning Mission learning used for analysis the data's and we can able to predict and we add some additional algorithm it's mainly used for prediction and AI.
Ans. 
Mission learning is used for data analysis and prediction with additional algorithms for AI.
• Mission learning is a subset of machine learning that focuses on predicting outcomes based on data analysis.

• It involves using algorithms to learn patterns and make predictions based on new data.

• Examples include image recognition, natural language processing, and recommendation systems.
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Q2. Deep learning uses: Deep learning Mainly used for creating artificial neurons in the neural network. Deep learning is very aid about the mission how to work and artificial intelligence helps also
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Q3. Statistics: Statistics is used for mathamatics operation and it helps to prediction. Example: We started to calculate how many persons live in between 20to25 age. That time statistics is very help to reduc...read more
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I don't know idea about group discussion

Basic DP, Array Questions

Q1. Resume Walkthrough and Discussion, Medium level coding questions
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Q1. Discussion with Manager
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Q1. Normal HR round
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Q1. What is multi collinearity?
Ans. 
Multicollinearity is a phenomenon where two or more independent variables in a regression model are highly correlated.
• It can lead to unstable and unreliable estimates of regression coefficients.

• It can also make it difficult to determine the individual effect of each independent variable on the dependent variable.

• It can be detected using methods such as correlation matrix, variance inflation factor (VIF), and eigenvalue...read more
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Q2. Machine learning algorithms - decsisin tree?
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Q3. Solve Try catch block
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Q1. Be ready to face interview by sharing your screen to write SQL queries for scenario based questions like joins,rank and dense rank, constraints,nested queries and questions like 3rd highest salary. For p...read more
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Q1. Manager round is like all scenario based questions like schedule refresh and project related questions like data connectivity sources, methodologies you are using, sprints,scrum meetings, BRD and FRD's.
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