FOCUS EDUMATICS Machine Learning Engineer Interview Questions and Answers

Contain question related to aptitude, pyrhon,ml mcqs.

Q1. What is overfitting and underfitting?
Ans. 
Overfitting occurs when a model learns the training data too well, leading to poor generalization. Underfitting happens when a model is too simple to capture the underlying patterns.
• Overfitting: Model performs well on training data but poorly on unseen data. Can be caused by a model being too complex or training for too long.

• Underfitting: Model is too simple to capture the underlying patterns in the data. Results in po...read more
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Q2. Explain about your project
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78 mcq questions with 2 coding questions in 1 hr 26 min.

Q1. Don't know about it.
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Q2. I was not selected.
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Aptitude round - Quant reasoning verbal

Three coding questions were given

Q1. Questions from project and some ml questions
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Q1. This was like technical and hr Questions from project
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Big data, aptitude, html, css, javascript, c language questions

Hackerrank coding test

OOP, aptitude, DSA, coding question-2 mcq and 1 code based

Q1. Pythons-OOP,DSA, basic questions
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Q2. Polymorphism, inheritance
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Q3. OOPs, 4 pillars of OOPs
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OOPs stands for Object-Oriented Programming and its 4 pillars are Inheritance, Encapsulation, Abstraction, and Polymorphism.
• Inheritance allows a class to inherit properties and behavior from another class.

• Encapsulation restricts access to certain components of an object, protecting its integrity.

• Abstraction hides complex implementation details and only shows the necessary features.

• Polymorphism allows objects to be trea...read more
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Q4. Dsa and python- Arrays,Stack, linked list,etc
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Q1. HR and technical question about ml, dl, cut the cake in 8 parts how will you do it.
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Questions on Quantitative, English and Logic.
Next section comprised of questions on SQL, OS, Java, HTML/CSS.
Last section had questions related to python and Machine learning and also couple of Coding questions whose level was Easy to moderate.

Q1. Name some evaluation metrics? What is precision and recall? Give some examples. What is Entropy and Gini impurity What are bagging techniques What are boosting techniques Difference between validation and ...read more
Ans. 
Explanation of evaluation metrics, precision, recall, entropy, Gini impurity, bagging, boosting, validation vs test data, LSTM, GRU, K-means clustering, and importing CSV datasets.
• Evaluation metrics: used to measure the performance of machine learning models (e.g., accuracy, precision, recall, F1 score)

• Precision: ratio of true positive predictions to the total predicted positives (TP / (TP + FP))

• Recall: ratio of true p...read more
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Q1. Tell me about yourself Where do you see yourself in next 5 years Why you want to join our company Soft skill questions like leadership, innovative thinker, problem solver etc. which are mentioned in the re...read more
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Q1. Actually after internship we will have evaluation.
Ans. So in evaluation they decide whether to continue or to extend your 4 month of internship. I got converted into FTE after 4 months.
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Q2. You need to showcase what u did in the internship As I converted to FTE from internship
Ans. U need to submit ur trakstar(evaluation) And u need to keep. Meet with mentor and they will rate you
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