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Talend Data Integration Services Ai Ml Engineer Interview Questions and Answers

Updated 19 Mar 2024

Talend Data Integration Services Ai Ml Engineer Interview Experiences

1 interview found

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

I applied via Job Portal and was interviewed in Sep 2023. There was 1 interview round.

Round 1 - One-on-one 

(1 Question)

  • Q1. Past Projects ,use case based problem solving

Interview questions from similar companies

Interview experience
3
Average
Difficulty level
-
Process Duration
-
Result
-
Round 1 - One-on-one 

(2 Questions)

  • Q1. Ask me on project
  • Q2. Aws, sql, python, flask ask me

Interview Preparation Tips

Interview preparation tips for other job seekers - Not selected
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 - One-on-one 

(2 Questions)

  • Q1. Question on NLP and Coding test
  • Q2. Maximum coding question from list and Regex
Round 3 - One-on-one 

(1 Question)

  • Q1. Project based question

Interview Preparation Tips

Interview preparation tips for other job seekers - Please prepare for Python coding question and Be prepare with your project
Interview experience
4
Good
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Approached by Company and was interviewed in Jul 2024. There were 2 interview rounds.

Round 1 - One-on-one 

(4 Questions)

  • Q1. Explain the ML project you recently worked?
  • Ans. 

    Developed a recommendation system for an e-commerce platform using collaborative filtering

    • Used collaborative filtering to analyze user behavior and recommend products

    • Implemented matrix factorization techniques to improve recommendation accuracy

    • Evaluated model performance using metrics like RMSE and precision-recall curves

  • Answered by AI
  • Q2. Questions related to ML fundamentals like supervised learning, unsupervised learning, evaluation and ML algorithms
  • Q3. Project specific questions
  • Q4. Easy-medium coding questions
Round 2 - HR 

(2 Questions)

  • Q1. What technologies you are working on?
  • Ans. 

    I am currently working on developing machine learning models using Python, TensorFlow, and scikit-learn.

    • Python programming language

    • TensorFlow framework

    • scikit-learn library

  • Answered by AI
  • Q2. How you will approach on machine learning problem?
  • Ans. 

    I would approach a machine learning problem by first understanding the problem, collecting and preprocessing data, selecting a suitable algorithm, training the model, evaluating its performance, and fine-tuning it.

    • Understand the problem statement and define the objectives clearly.

    • Collect and preprocess the data to make it suitable for training.

    • Select a suitable machine learning algorithm based on the problem type (clas...

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Focus on your skill and project which you worked on

Skills evaluated in this interview

Interview experience
3
Average
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Not Selected

I applied via Naukri.com and was interviewed in Jan 2024. There was 1 interview round.

Round 1 - Technical 

(1 Question)

  • Q1. Q. explain your project Q. Project-related questions asked basic to hard Q. What is backpropagation in deep learning? Q. What is the Hugging Face module and working Q. Object detection YOLO NAS Vs YOLO 8

Interview Preparation Tips

Interview preparation tips for other job seekers - interview medium not much hard
Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
Not Selected
Round 1 - Group Discussion 

Discussion on Gradient, SGD, K Mean ++, Silhouette Score, How to Handle High Variation Data,
Coding asked to code KNN, Hyper-Parameter Tuning, Two Difficult Questions on Coding...DSA Based Stumped on Those.

Verdict... Not Selected

Round 2 - Coding Test 

Simple Coding No Chat GPT Support Should Be There

Interview Preparation Tips

Interview preparation tips for other job seekers - Python DSA + Some Sort of Online TCS YouTube Videos.
Interview experience
4
Good
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
No response

I applied via Naukri.com and was interviewed in Dec 2024. There was 1 interview round.

Round 1 - Technical 

(1 Question)

  • Q1. Difference between Lemmatization and stemming
  • Ans. 

    Lemmatization produces the base or dictionary form of a word, while stemming reduces words to their root form.

    • Lemmatization considers the context and meaning of the word, resulting in a valid word that makes sense.

    • Stemming simply chops off prefixes or suffixes, potentially resulting in non-existent words.

    • Example: Lemmatization of 'better' would result in 'good', while stemming would reduce it to 'bet'.

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

I applied via Company Website and was interviewed in Jul 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 - HR 

(1 Question)

  • Q1. Normal HR round that happens as the initial screening process
Round 3 - Coding Test 

Python basic coding questions (pandas, numpy, OOPs concept.
AI ML theory questions

Round 4 - HR 

(1 Question)

  • Q1. Normal salary discussion
Interview experience
3
Average
Difficulty level
Moderate
Process Duration
-
Result
No response

I was interviewed in Oct 2024.

Round 1 - Technical 

(3 Questions)

  • Q1. What is OHE ( one hot encoding)
  • Ans. 

    OHE is a technique used in machine learning to convert categorical data into a binary format.

    • OHE is used to convert categorical variables into a format that can be provided to ML algorithms.

    • Each category is represented by a binary vector where only one element is 'hot' (1) and the rest are 'cold' (0).

    • For example, if we have a 'color' feature with categories 'red', 'blue', 'green', OHE would represent them as [1, 0, 0],

  • Answered by AI
  • Q2. What is conditional probability
  • Ans. 

    Conditional probability is the likelihood of an event occurring given that another event has already occurred.

    • Conditional probability is calculated using the formula P(A|B) = P(A and B) / P(B)

    • It represents the probability of event A happening, given that event B has already occurred

    • Conditional probability is used in various fields such as machine learning, statistics, and finance

  • Answered by AI
  • Q3. What is precision, recall
  • Ans. 

    Precision and recall are evaluation metrics used in machine learning to measure the performance of a classification model.

    • Precision is the ratio of correctly predicted positive observations to the total predicted positive observations.

    • Recall is the ratio of correctly predicted positive observations to the all observations in actual class.

    • Precision is important when the cost of false positives is high, while recall is i...

  • Answered by AI

Skills evaluated in this interview

Interview experience
4
Good
Difficulty level
-
Process Duration
-
Result
-
Round 1 - One-on-one 

(2 Questions)

  • Q1. What is zip function
  • Ans. 

    The zip function in Python is used to combine multiple iterables into a single iterable of tuples.

    • Zip function takes two or more iterables as arguments and returns an iterator of tuples where the i-th tuple contains the i-th element from each of the input iterables.

    • If the input iterables are of different lengths, the resulting iterator will only have as many elements as the shortest input iterable.

    • Example: zip([1, 2, 3...

  • Answered by AI
  • Q2. What is NLP in Machine learning
  • Ans. 

    NLP (Natural Language Processing) in machine learning is the ability of a computer to understand, interpret, and generate human language.

    • NLP enables machines to analyze and derive meaning from human language data.

    • It involves tasks such as text classification, sentiment analysis, named entity recognition, and machine translation.

    • Examples of NLP applications include chatbots, language translation services, and speech rec

  • Answered by AI

Skills evaluated in this interview

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Talend Data Integration Services Interview FAQs

How many rounds are there in Talend Data Integration Services Ai Ml Engineer interview?
Talend Data Integration Services interview process usually has 1 rounds. The most common rounds in the Talend Data Integration Services interview process are One-on-one Round.

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Talend Data Integration Services Ai Ml Engineer Interview Process

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