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I applied via Recruitment Consulltant and was interviewed in Feb 2024. There was 1 interview round.
L1 and L2 regularization are techniques used in machine learning to prevent overfitting by adding penalty terms to the cost function.
L1 regularization adds the absolute values of the coefficients as penalty term to the cost function.
L2 regularization adds the squared values of the coefficients as penalty term to the cost function.
L1 regularization can lead to sparse models by forcing some coefficients to be exactly zer...
I applied via Campus Placement and was interviewed before Sep 2020. There were 3 interview rounds.
Code for parsing a triangle
Use a loop to iterate through each line of the triangle
Split each line into an array of numbers
Store the parsed numbers in a 2D array or a list of lists
The ASCII value is a numerical representation of a character. It includes both capital and small alphabets.
ASCII values range from 65 to 90 for capital letters A to Z.
ASCII values range from 97 to 122 for small letters a to z.
For example, the ASCII value of 'A' is 65 and the ASCII value of 'a' is 97.
I applied via Recruitment Consultant and was interviewed in Sep 2020. There were 3 interview rounds.
I applied via Recruitment Consultant and was interviewed in Mar 2021. There was 1 interview round.
I applied via Naukri.com and was interviewed before Oct 2022. There were 4 interview rounds.
Coding round basic packages , and basic python coding
I applied via Approached by Company and was interviewed before Feb 2023. There was 1 interview round.
Hypothesis testing is a statistical method used to make inferences about a population based on sample data.
It involves formulating a hypothesis about a population parameter, collecting data, and using statistical tests to determine if the data supports or rejects the hypothesis.
There are two types of hypotheses: null hypothesis (H0) and alternative hypothesis (H1).
Common statistical tests for hypothesis testing include...
Null hypothesis is a statement that there is no significant difference or relationship between variables being studied.
Null hypothesis is typically denoted as H0 in statistical hypothesis testing.
It is the default assumption that there is no effect or relationship.
The alternative hypothesis (Ha) is the opposite of the null hypothesis.
For example, in a study testing a new drug, the null hypothesis would be that the drug...
Supervised learning uses labeled data to train a model, while unsupervised learning uses unlabeled data.
Supervised learning requires labeled data for training
Unsupervised learning does not require labeled data
Examples of supervised learning include classification and regression
Examples of unsupervised learning include clustering and dimensionality reduction
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