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I applied via Company Website and was interviewed in Jan 2024. There were 2 interview rounds.
Related to Mathematical intuition in Deep learning.
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Approach involves data preprocessing, model training, evaluation, and interpretation.
Perform data preprocessing such as handling missing values, encoding categorical variables, and scaling features.
Split the data into training and testing sets.
Train the logistic regression model on the training data.
Evaluate the model using metrics like accuracy, precision, recall, and F1 score.
Interpret the model coefficients to under...
I would seek opportunities to apply my skills in related fields within the company.
Explore other departments or teams within the company that may have projects related to my field of interest
Offer to collaborate with colleagues in different departments to bring a new perspective to their projects
Seek out professional development opportunities to expand my skills and knowledge in related areas
Bagging and boosting are ensemble learning techniques used to improve the performance of machine learning models.
Bagging (Bootstrap Aggregating) involves training multiple models independently on different subsets of the training data and then combining their predictions through averaging or voting.
Boosting involves training multiple models sequentially, where each subsequent model corrects the errors made by the previ...
How to judge if the comment is actually describing a product
Business Related case study, signed NDA
I applied via Campus Placement and was interviewed before Apr 2023. There were 2 interview rounds.
I applied via Approached by Company and was interviewed before Sep 2021. There were 3 interview rounds.
Explain dynamic programming with memoization
2 Question and live coding was conducted on self platform
based on 1 interview
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based on 1 review
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