Exl India Data Scientist Interview Questions and Answers

It was on python ,SQL ,logical reasoning and quant

Case study was given on a business scenario

Q1. Technical questions based on cv related to ML project And HR question
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Q2. What is cross validation explain in layman term What is precision What is confusion Matrix draw with dummy data
Ans. 
Cross validation is a technique to evaluate the performance of a model by splitting the data into multiple subsets.
• Cross validation helps in assessing how well a model generalizes to new data.

• It involves splitting the data into training and testing sets multiple times to get a more reliable estimate of model performance.

• Common types of cross validation include k-fold cross validation and leave-one-out cross validation.
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Q3. Tell me a situation where your opinion came to help
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Q4. Draw confusion Matrix on board
Ans. 
Confusion Matrix is a table used to describe the performance of a classification model.
• Confusion Matrix is a 2x2 table with Actual and Predicted values

• It consists of True Positive, True Negative, False Positive, and False Negative

• Example: TP=100, TN=50, FP=10, FN=5

• Accuracy = (TP + TN) / (TP + TN + FP + FN)

• Precision = TP / (TP + FP)

• Recall = TP / (TP + FN)
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Q5. Project related questions - objective,reuslts
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It was 45 min interview based on mathematical, probablity, statistical, machine leaning based questions

It has SAS python SQL aptitude logic

Was given a case study on how should fedex should grow inorganic or organic

Q1. Related to Machine learning and HR What is overfitting?
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Q2. What is cross validation
Ans. 
Cross validation is a technique used to evaluate the performance of a machine learning model by testing it on multiple subsets of the data.
• It involves dividing the data into multiple subsets or folds.

• The model is trained on a subset and tested on the remaining subset.

• This process is repeated for all subsets and the results are averaged to get a final performance metric.

• It helps to prevent overfitting and provides a mor...read more
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Q3. What is confusion matrix
Ans. 
A confusion matrix is a table used to evaluate the performance of a classification model.
• It shows the number of true positives, true negatives, false positives, and false negatives.

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

• It is useful in comparing the performance of different models.

• Example: A confusion matrix for a binary classification problem can be represente...read more
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