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Foundation AI
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I applied via Approached by Company and was interviewed in Sep 2024. There was 1 interview round.
I applied via Approached by Company and was interviewed in Nov 2024. There were 3 interview rounds.
Developing frameworks for organizational culture.
Operational Efficiency Framework
I applied via Job Portal
I applied via Naukri.com and was interviewed in Nov 2022. There were 4 interview rounds.
Foundation AI interview questions for popular designations
I applied via Approached by Company and was interviewed before Dec 2023. There were 2 interview rounds.
After 1 round they are taking assignment round in tht they are give you login credentials of their AI app then you need to create pom classes and test classes for scenarios like file upload handle drop-down and many more finding the web element by using xpath by axes
I prefer not to disclose my current CTC. As for my expectation, I am looking for a competitive salary based on my skills and experience.
I am open to discussing compensation based on the job requirements and my qualifications
I am looking for a salary that is competitive with industry standards
I am willing to negotiate based on the overall compensation package
I am looking for a fair compensation that reflects my skills a...
I applied via LinkedIn and was interviewed before Feb 2022. There were 4 interview rounds.
My area of expertise is in machine learning and deep learning. I specialize in Foundation AI because it is the backbone of modern AI.
I have extensive experience in developing and implementing machine learning models for various applications.
I have a strong understanding of the underlying principles of deep learning and how it can be used to solve complex problems.
Foundation AI is important because it provides the funda...
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posted on 30 Sep 2024
20 MCQ questions related to Data science and 1 coding ML question.
Overfitting and underfitting are common problems in machine learning where a model performs too well on training data but poorly on unseen data, or performs poorly on both training and unseen data due to oversimplification.
Overfitting occurs when a model learns the noise in the training data rather than the underlying pattern, leading to poor generalization on unseen data.
Underfitting happens when a model is too simple...
K-fold CV is a technique used to evaluate the performance of a machine learning model by splitting the data into k subsets.
Data is divided into k subsets, with one subset used as the validation set and the rest as training sets.
The process is repeated k times, with each subset used once as the validation data.
The average of the k validation results is used as the final performance metric.
Helps in reducing bias and vari...
I applied via Approached by Company and was interviewed before Sep 2022. There were 3 interview rounds.
Ridge and Lasso regression are both regularization techniques used in linear regression to prevent overfitting.
Ridge regression adds a penalty equivalent to the square of the magnitude of coefficients, while Lasso regression adds a penalty equivalent to the absolute value of the magnitude of coefficients.
Ridge regression shrinks the coefficients towards zero but never exactly to zero, while Lasso regression can shrink ...
Boosting focuses on improving the performance of weak learners sequentially, while bagging uses parallel ensemble learning with bootstrapping.
Boosting combines multiple weak learners to create a strong learner by giving more weight to misclassified instances in each iteration.
Bagging creates multiple subsets of the training data through bootstrapping and trains each subset independently to reduce variance.
Examples: Ada...
The duration of Foundation AI interview process can vary, but typically it takes about less than 2 weeks to complete.
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