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I was interviewed in Aug 2020.
I applied via Facultytick and was interviewed in May 2024. There was 1 interview round.
The difficult session involved addressing challenging behavior and lack of motivation among trainees.
Focused on identifying root causes of behavior and motivation issues
Implemented personalized strategies to address individual needs
Used positive reinforcement and encouragement to boost morale
Provided additional support and resources for struggling trainees
National Institute of Technology interview questions for popular designations
I applied via Walk-in and was interviewed in Aug 2023. There were 2 interview rounds.
It was a Gate exam, conducted by central government. One have to get minimum cutoff for eligibility
Average unit weight of soil is the weight of soil per unit volume.
Average unit weight of soil is typically measured in pounds per cubic foot (pcf) or kilonewtons per cubic meter (kN/m^3).
It is influenced by factors such as moisture content, compaction, and type of soil.
For example, the average unit weight of dry sand is around 100 pcf, while the average unit weight of saturated clay is around 120 pcf.
Easy basic questions
Output program in C python and so many data science company so many internship and job oppertunities.
I applied via Campus Placement and was interviewed before Mar 2023. There were 2 interview rounds.
Basic questions were asked
Basic and advanced coding
I applied via Company Website and was interviewed before Apr 2022. There were 2 interview rounds.
I applied via Company Website and was interviewed in Jun 2021. There was 1 interview round.
Type I error is rejecting a true null hypothesis, while Type II error is failing to reject a false null hypothesis.
Type I error is also known as a false positive.
Type II error is also known as a false negative.
Type I error occurs when the researcher concludes that there is a significant effect when there is not.
Type II error occurs when the researcher concludes that there is no significant effect when there actually is...
Regularization is a technique used to prevent overfitting in machine learning models.
Regularization adds a penalty term to the loss function to discourage complex models.
It helps to reduce the variance of the model and improve its generalization performance.
L1 and L2 regularization are commonly used techniques.
L1 regularization adds the absolute value of the coefficients to the loss function.
L2 regularization adds the ...
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Research Scholar
168
salaries
| ₹3 L/yr - ₹7.2 L/yr |
PHD Research Scholar
81
salaries
| ₹3 L/yr - ₹7.2 L/yr |
Senior Research Fellow
75
salaries
| ₹3.3 L/yr - ₹8 L/yr |
Assistant Professor
40
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| ₹4 L/yr - ₹13.8 L/yr |
Junior Research Fellow
40
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| ₹2.3 L/yr - ₹6 L/yr |
Indian Institute of Technology BHU
Indian Institute of Science
Birla Institute of Technology, Mesra
Indian Statistical Institute