Upload Button Icon Add office photos

Filter interviews by

Clear (1)

TuringMinds Machine Learning Analyst Interview Questions and Answers

Updated 29 May 2023

TuringMinds Machine Learning Analyst Interview Experiences

2 interviews found

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Campus Placement and was interviewed in Apr 2023. There were 4 interview rounds.

Round 1 - Resume Shortlist 
Pro Tip by AmbitionBox:
Keep your resume crisp and to the point. A recruiter looks at your resume for an average of 6 seconds, make sure to leave the best impression.
View all Resume tips
Round 2 - Aptitude Test 

English, maths, statistics, aptitude

Round 3 - Jam 

(2 Questions)

  • Q1. Topic will be given before 5 minutes. You need to talk for a minute or more
  • Q2. Role of women in corporate world
  • Ans. 

    Women play a crucial role in the corporate world.

    • Women bring diverse perspectives and ideas to the table, leading to better decision-making and innovation.

    • They also contribute to a more inclusive and equitable workplace culture.

    • Studies have shown that companies with more women in leadership positions tend to have better financial performance.

    • However, women still face challenges such as gender bias and unequal pay in th

  • Answered by AI
Round 4 - One-on-one 

(1 Question)

  • Q1. Here technical questions and general questions were asked

Interview Preparation Tips

Topics to prepare for TuringMinds Machine Learning Analyst interview:
  • Statistics
  • Python
  • Maths
Interview preparation tips for other job seekers - Knowledge in Statistics, mathematics, Python and good communication skills are required
Round 1 - Aptitude Test 

It's all about mathematics, statistics, general knowledge

Round 2 - Group Discussion 

Impact on social media

Round 3 - Technical 

(1 Question)

  • Q1. Based on my resume,and about cloud computing
Round 4 - HR 

(1 Question)

  • Q1. Discussed about academic and personal information,and about CTC

Interview Preparation Tips

Interview preparation tips for other job seekers - Prepare well to get a dream job.be polite and use the right language and tone for a formal situation. listen to the questions and think before you begin your answers. ask the interviewer to repeat or explain further if you do not understand a question. use the STAR method to answer questions about your skills and experience

Machine Learning Analyst Interview Questions Asked at Other Companies

Interview questions from similar companies

Interview Questionnaire 

1 Question

  • Q1. What friends think of you?
  • Ans. 

    My friends think of me as reliable, supportive, and always up for a good time.

    • Reliable - always there when they need help or support

    • Supportive - willing to listen and offer advice

    • Fun-loving - enjoys socializing and trying new things

  • Answered by AI

Interview Preparation Tips

Round: Resume Shortlist
Experience: After Resume Shortlist we had an aptitute round.
Tips: Answer according to your own judgement. Dont try to be too precise.

Round: HR Interview
Experience: I said they think I am a workaholic as I prefer to complete my work before chilling with them.

College Name: NIT Durgapur

Interview Preparation Tips

Round: HR Interview
Experience: Interview at 11 pm. Stressed environment, close to stress interview.
SELECTION PROCEDURE:
1.Online Test
2. GD
3. PI(HR)
GD TOPICS :
Topic 1 : How can education system benefit from interdisciplinary methods.
Topic 2 : Interconnected problems in the field of movie making.
INTERVIEW EXPERIENCE:
So you can speak German? Describe MS Dhoni in german. They opened Google Translate to counter check the words they wanted to be translated in both Deutsch and Spanish. Your profile speaks of an inclination towards software skills, why do you want to join an analytics company? Justify your action in two reasons as to why are you sitting here interviewing for the post of a data scientist rather than apply for a software engineer when this CV speaks highly of computer science? What is Finite Element Method? Explain. How relevant is your work in Computer Vision? Breakdown the tagline of Audi and translate accordingly. What is "Technik für Mobel" ? What are your current projects? Answer : Microsoft Xbox Kinect, Gesture Recognition. Counter question : But at Musimga you'd be doing far simpler stuff.? Counter suggestion : Why don't you go for MS?


Tips: Keep your cool during counter questions. Prepare your profile and CV well. Rest all is your hard work and groomed personal talents and acquired skills you learnt over the internet.

Skills: Ability To Cope Up With Stress, Spanish, German, Finite Element Modeling - FEM, Foreign Language
College Name: NIT Raipur
Funny Moments: Another HR enters in the midst of my interview and asks with bewildered amazement : What language is he speaking?
The other HR, "German".

I applied via Recruitment Consultant and was interviewed in Dec 2018. There were 3 interview rounds.

Interview Questionnaire 

11 Questions

  • Q1. 1. Why Machine Learning?
  • Q2. 2. Why did you choose Data Science Field?
  • Ans. 

    I chose Data Science field because of its potential to solve complex problems and make a positive impact on society.

    • Fascination with data and its potential to drive insights

    • Desire to solve complex problems and make a positive impact on society

    • Opportunity to work with cutting-edge technology and tools

    • Ability to work in a variety of industries and domains

    • Examples: Predictive maintenance in manufacturing, fraud detection

  • Answered by AI
  • Q3. 3. What about Linear Regression? (Theory Part)
  • Q4. 4. What is the difference between Linear Regression and Logistic Regression?
  • Ans. 

    Linear Regression is used for predicting continuous numerical values, while Logistic Regression is used for predicting binary categorical values.

    • Linear Regression predicts a continuous output, while Logistic Regression predicts a binary output.

    • Linear Regression uses a linear equation to model the relationship between the independent and dependent variables, while Logistic Regression uses a logistic function.

    • Linear Regr...

  • Answered by AI
  • Q5. 5. Explain Confusion Matrix?
  • Ans. 

    Confusion matrix is a table used to evaluate the performance of a classification model.

    • It is a 2x2 matrix that shows the number of true positives, false positives, true negatives, and false negatives.

    • It helps in calculating various metrics like accuracy, precision, recall, and F1 score.

    • It is useful in identifying the strengths and weaknesses of a model and improving its performance.

    • Example: In a binary classification p...

  • Answered by AI
  • Q6. 6. Can we use confusion matrix in Linear Regression?
  • Ans. 

    No, confusion matrix is not used in Linear Regression.

    • Confusion matrix is used to evaluate classification models.

    • Linear Regression is a regression model, not a classification model.

    • Evaluation metrics for Linear Regression include R-squared, Mean Squared Error, etc.

  • Answered by AI
  • Q7. 7. Explain KNN Algorithm?
  • Ans. 

    KNN is a non-parametric algorithm used for classification and regression tasks.

    • KNN stands for K-Nearest Neighbors.

    • It works by finding the K closest data points to a given test point.

    • The class or value of the test point is then determined by the majority class or average value of the K neighbors.

    • KNN can be used for both classification and regression tasks.

    • It is a simple and easy-to-understand algorithm, but can be compu

  • Answered by AI
  • Q8. 8. Explain Random Forest and Decision Tree?
  • Ans. 

    Random Forest is an ensemble learning method that builds multiple decision trees and combines their outputs to improve accuracy.

    • Random Forest is a type of supervised learning algorithm used for classification and regression tasks.

    • It creates multiple decision trees and combines their outputs to make a final prediction.

    • Each decision tree is built using a random subset of features and data points to reduce overfitting.

    • Ran...

  • Answered by AI
  • Q9. 9. One Tricky Mathematical Question !
  • Q10. 10. What are the Projects you have done?
  • Ans. 

    I have worked on various projects involving data analysis, machine learning, and predictive modeling.

    • Developed a predictive model to forecast customer churn for a telecommunications company.

    • Built a recommendation system using collaborative filtering for an e-commerce platform.

    • Performed sentiment analysis on social media data to understand customer opinions and preferences.

    • Implemented a fraud detection system using anom...

  • Answered by AI
  • Q11. I didn't get shortlisted for 2nd Round.

Interview Preparation Tips

General Tips: anyone who wants to go in data science field should actually be interested in the field not the money. They should be good in Statistics, Probability and Theory part of ML algorithms.
They will ask you about the projects you have mentioned in resume and all the questions will be from that part.
Skills: Communication, Body Language, Problem Solving, Analytical Skills
Duration: 1-4 weeks

Skills evaluated in this interview

Data Scientist Interview Questions & Answers

C5i user image Kushal Kulkarni

posted on 18 Jun 2024

Interview experience
5
Excellent
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
Not Selected

I was interviewed in May 2024.

Round 1 - Assignment 

Questions based on ML,PYTHON, DATA VISUALIZATION

Round 2 - Technical 

(2 Questions)

  • Q1. What is TF-IDF IN NLP
  • Ans. 

    TF-IDF is a numerical statistic that reflects the importance of a word in a document relative to a collection of documents.

    • TF-IDF stands for Term Frequency-Inverse Document Frequency

    • It is used in Natural Language Processing (NLP) to determine the importance of a word in a document

    • TF-IDF is calculated by multiplying the term frequency (TF) by the inverse document frequency (IDF)

    • It helps in identifying the most important

  • Answered by AI
  • Q2. Python coding questions based on list

Interview Preparation Tips

Interview preparation tips for other job seekers - Practice python
Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Assignment 

ML,DL,Python,NLP,Data VIsualization

Round 2 - Technical 

(1 Question)

  • Q1. Explain TF-IDF in NLP
  • Ans. 

    TF-IDF is a numerical statistic that reflects the importance of a word in a document relative to a collection of documents.

    • TF-IDF stands for Term Frequency-Inverse Document Frequency.

    • It is used in Natural Language Processing (NLP) to determine the importance of a word in a document.

    • TF-IDF is calculated by multiplying the term frequency (TF) of a word by the inverse document frequency (IDF) of the word.

    • It helps in ident...

  • Answered by AI
Interview experience
5
Excellent
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Naukri.com and was interviewed before Dec 2023. There were 3 interview rounds.

Round 1 - Coding Test 

Test of Basic data structures in Python include lists, tuples, and dictionaries, as well as loops and conditional statements.

Round 2 - Case Study 

Framework and requirements for chatbot implementation.

Round 3 - HR 

(1 Question)

  • Q1. Salary discussion
Interview experience
4
Good
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
Not Selected

I applied via Campus Placement and was interviewed in Aug 2024. There were 2 interview rounds.

Round 1 - Aptitude Test 

Aptitude test consists of 40 questions.

Round 2 - HR 

(2 Questions)

  • Q1. Introduce yourself with ur projects
  • Ans. 

    I am a data scientist with experience in developing predictive models and analyzing large datasets.

    • Developed a predictive model for customer churn prediction using machine learning algorithms

    • Analyzed sales data to identify key trends and patterns for business optimization

    • Implemented natural language processing techniques for sentiment analysis of customer reviews

  • Answered by AI
  • Q2. Problem statement of a case that needs solutions.
  • Ans. 

    Develop a predictive model to identify potential customers for a new product launch.

    • Define the target variable and features to be used in the model

    • Collect and preprocess relevant data for training the model

    • Select an appropriate machine learning algorithm and train the model

    • Evaluate the model's performance using metrics like accuracy, precision, and recall

    • Use the model to predict potential customers for the new product

  • Answered by AI
Interview experience
4
Good
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Resume Shortlist 
Pro Tip by AmbitionBox:
Keep your resume crisp and to the point. A recruiter looks at your resume for an average of 6 seconds, make sure to leave the best impression.
View all Resume tips
Round 2 - Coding Test 

Basic test with Data Structures, algorithms, SQL questions

Round 3 - Technical 

(1 Question)

  • Q1. Questions about basic ML Algorithms
Contribute & help others!
anonymous
You can choose to be anonymous

TuringMinds Interview FAQs

How many rounds are there in TuringMinds Machine Learning Analyst interview?
TuringMinds interview process usually has 4 rounds. The most common rounds in the TuringMinds interview process are Aptitude Test, Group Discussion and Technical.
What are the top questions asked in TuringMinds Machine Learning Analyst interview?

Some of the top questions asked at the TuringMinds Machine Learning Analyst interview -

  1. Topic will be given before 5 minutes. You need to talk for a minute or m...read more
  2. Here technical questions and general questions were as...read more
  3. Based on my resume,and about cloud comput...read more

Recently Viewed

INTERVIEWS

Becton Dickinson

No Interviews

CAMPUS PLACEMENT

KIIT University, Bhuvaneshwar

INTERVIEWS

TuringMinds

No Interviews

INTERVIEWS

Becton Dickinson

No Interviews

INTERVIEWS

Arvind Group

No Interviews

INTERVIEWS

Arvind Group

No Interviews

INTERVIEWS

Becton Dickinson

No Interviews

INTERVIEWS

Becton Dickinson

No Interviews

INTERVIEWS

TuringMinds

No Interviews

INTERVIEWS

Apexon

No Interviews

Tell us how to improve this page.

TuringMinds Machine Learning Analyst Interview Process

based on 1 interview

Interview experience

4
  
Good
View more

Interview Questions from Similar Companies

TCS Interview Questions
3.7
 • 10.4k Interviews
Accenture Interview Questions
3.8
 • 8.1k Interviews
Infosys Interview Questions
3.6
 • 7.5k Interviews
Wipro Interview Questions
3.7
 • 5.6k Interviews
Cognizant Interview Questions
3.8
 • 5.6k Interviews
Amazon Interview Questions
4.1
 • 5k Interviews
Capgemini Interview Questions
3.7
 • 4.7k Interviews
Tech Mahindra Interview Questions
3.5
 • 3.8k Interviews
HCLTech Interview Questions
3.5
 • 3.8k Interviews
Genpact Interview Questions
3.8
 • 3.1k Interviews
View all
TuringMinds Machine Learning Analyst Salary
based on 5 salaries
₹1 L/yr - ₹5.2 L/yr
44% less than the average Machine Learning Analyst Salary in India
View more details
Data Scientist
144 salaries
unlock blur

₹0 L/yr - ₹0 L/yr

Data Scientist Trainee
52 salaries
unlock blur

₹0 L/yr - ₹0 L/yr

Data Science Trainee
23 salaries
unlock blur

₹0 L/yr - ₹0 L/yr

Machine Learning Engineer
12 salaries
unlock blur

₹0 L/yr - ₹0 L/yr

Data Analyst
9 salaries
unlock blur

₹0 L/yr - ₹0 L/yr

Explore more salaries
Compare TuringMinds with

Fractal Analytics

4.0
Compare

Mu Sigma

2.6
Compare

Tredence

3.6
Compare

LatentView Analytics

3.7
Compare
Did you find this page helpful?
Yes No
write
Share an Interview