Ekart Logistics Learning & Development Specialist Interview Questions and Answers

Questions were mix of mcq and coding in which coding was easy to medium level.

Q1. A breif intro about me
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Q2. My resume especially my projects and tech stacks used in it
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Q1. What is confusion matrix and why it is used
Ans. 
Confusion matrix is a table used to evaluate the performance of a classification model.
• It is used to visualize the performance of a machine learning model by comparing actual and predicted values.

• It consists of four sections: true positive, false positive, true negative, and false negative.

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

• Example: In a binary classification problem,...read more
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Q2. How to handle imbalance dataset
Ans. 
Handling imbalance dataset involves techniques like resampling, using different algorithms, and adjusting class weights.
• Use resampling techniques like oversampling or undersampling to balance the dataset

• Utilize algorithms that are robust to class imbalance such as Random Forest, Gradient Boosting, or SVM

• Adjust class weights in the model to give more importance to minority class
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Q1. What are projects you have done and what is the use case
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Q1. Tell me about your self
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Experienced Learning & Development Specialist with a passion for creating engaging training programs.
• Over 5 years of experience in designing and delivering training programs

• Strong background in instructional design and adult learning principles

• Skilled in conducting needs assessments and evaluating training effectiveness

• Proficient in using learning management systems and e-learning tools

• Excellent communication and p
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Q2. Why we should hire you
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Q1. About machine learning basics and on resume
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Q1. About resume and deep learning a bit off
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Q1. I didn't make up to HR round
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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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It was an easy one with basic aptitude and basics of programming

Good level of coding questions

Q1. What is machine learning
Ans. 
Machine learning is a subset of artificial intelligence that involves the development of algorithms and statistical models to perform specific tasks without explicit instructions.
• Machine learning is a subset of artificial intelligence.

• It involves the development of algorithms and statistical models.

• These models are trained on data to make predictions or decisions.

• Examples include image recognition, natural language pro
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Q2. Types of machine learning and difference between ML and deep learning
Ans. 
Types of machine learning include supervised, unsupervised, and reinforcement learning. Deep learning is a subset of ML using neural networks.
• Supervised learning: Uses labeled data to make predictions, such as classification or regression.

• Unsupervised learning: Finds patterns in unlabeled data, like clustering or dimensionality reduction.

• Reinforcement learning: Learns through trial and error to maximize rewards, common...read more
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Q1. Resume questions
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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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