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I applied via Walk-in
I analyze various factors such as revenue growth, market share, competitive landscape, and future prospects to determine the valuation of technology companies.
I research and analyze financial statements, industry reports, and market trends.
I consider the company's revenue growth, market share, and competitive landscape.
I evaluate the company's future prospects and potential for innovation.
I use various valuation method...
I applied via Job Portal and was interviewed in Nov 2021. There was 1 interview round.
Bank of America Securities interview questions for popular designations
I applied via Referral
Top trending discussions
posted on 15 Mar 2024
I applied via Company Website and was interviewed before Mar 2023. There were 3 interview rounds.
Strings and array concepts
I applied via Company Website and was interviewed before Feb 2023. There were 2 interview rounds.
Difficulty level - medium
To improve model performance beyond hyperopt, consider ensemble methods, feature engineering, and data augmentation.
Implement ensemble methods like bagging, boosting, or stacking to combine multiple models.
Perform feature engineering to create new informative features or transform existing ones.
Apply data augmentation techniques to increase the size and diversity of the training data.
Consider using advanced algorithms ...
XGBoost is an optimized version of Gradient Boosting Machine (GBM) with additional features and improvements.
XGBoost is a scalable and efficient implementation of gradient boosting algorithm.
XGBoost uses a more regularized model formalization to control overfitting.
XGBoost supports parallel processing and can handle large datasets.
XGBoost provides built-in regularization techniques like L1 and L2 regularization.
XGBoost...
To tune model performance, adjust hyperparameters, preprocess data, increase training data, and use ensemble methods.
Adjust hyperparameters such as learning rate, regularization, and batch size.
Preprocess data by scaling, normalizing, or handling missing values.
Increase training data to reduce overfitting and improve generalization.
Use ensemble methods like bagging or boosting to combine multiple models.
Perform cross-v...
Handling class imbalance involves techniques such as resampling, adjusting class weights, and using ensemble methods.
Resampling techniques like oversampling the minority class or undersampling the majority class can help balance the classes.
Adjusting class weights during model training can give more importance to the minority class.
Using ensemble methods like bagging or boosting can improve the performance on imbalance...
I applied via Approached by Company and was interviewed in Jan 2024. There were 3 interview rounds.
Medium to easy level leetcode question
Medium question coderpad round
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Goldman Sachs
Morgan Stanley
Joannou & Paraskevaides
Citi Group Global Markets