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I applied via Recruitment Consulltant and was interviewed before Jul 2023. There were 4 interview rounds.
Aptitude test - lr questions
Technical questions sql
To find the join result of two tables, you can use SQL JOIN statement.
Use SQL JOIN statement to combine rows from two or more tables based on a related column between them.
Types of joins include INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN.
Example: SELECT * FROM table1 INNER JOIN table2 ON table1.column = table2.column;
I was interviewed in Dec 2024.
Normal aptitude round
I applied via Approached by Company and was interviewed in May 2024. There were 3 interview rounds.
DSA was asked. And general coding language questions were asked. Previous experience based questions were asked.
Machine Learning, Generative AI, Deep learning interview questions. 2 Coding problems based on Algorithms.
I applied via Approached by Company and was interviewed in Oct 2024. There were 2 interview rounds.
Combination logic on python
Classification is a machine learning technique used to categorize data into different classes or categories based on past observations.
Classification involves training a model on labeled data to predict the class of new, unseen data points.
Common algorithms for classification include logistic regression, decision trees, support vector machines, and k-nearest neighbors.
Examples of classification tasks include spam email...
Machine Learning, Metrics
I applied via Naukri.com and was interviewed in Sep 2023. There were 3 interview rounds.
I applied via Approached by Company and was interviewed before Sep 2023. There were 3 interview rounds.
Simple Data Science Case Study
Data Science Case Study
It was on HackerRank
Building a reward points model.
Precision is the ratio of correctly predicted positive observations to the total predicted positives, while recall is the ratio of correctly predicted positive observations to the all observations in actual class.
Precision focuses on the accuracy of positive predictions, while recall focuses on the proportion of actual positives that were correctly identified.
Precision = TP / (TP + FP), Recall = TP / (TP + FN)
High prec...
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