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Step function is a function that returns a constant value for a certain range of inputs.
In machine learning, step functions are used as activation functions in neural networks.
They are typically used in binary classification problems where the output is either 0 or 1.
Examples include Heaviside step function and sigmoid step function.
Investigate the model performance metrics and adjust the threshold for classification.
Analyze the confusion matrix to understand the distribution of false positives.
Adjust the threshold for classification to reduce false positives.
Consider using different evaluation metrics like precision, recall, and F1 score.
Explore feature importance to identify variables contributing to false positives.
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I was interviewed in Mar 2023.
I applied via LinkedIn and was interviewed in Oct 2021. There were 5 interview rounds.
I applied via LinkedIn and was interviewed in Oct 2021. There were 5 interview rounds.
Machine learning evaluation metrics are used to measure the performance of a model.
Accuracy
Precision
Recall
F1 Score
ROC Curve
AUC
Confusion Matrix
Mean Squared Error
Root Mean Squared Error
R-squared
I applied via Job Portal and was interviewed in Aug 2023. There were 2 interview rounds.
Aptitude test for about an hour.
Parameters used in a random forest include number of trees, maximum depth of trees, minimum samples split, and maximum features.
Number of trees: The number of decision trees to be used in the random forest.
Maximum depth of trees: The maximum depth allowed for each decision tree.
Minimum samples split: The minimum number of samples required to split a node.
Maximum features: The maximum number of features to consider when
I applied via Naukri.com and was interviewed in Jul 2024. There was 1 interview round.
Sigmoid function is a mathematical function that maps any real value to a value between 0 and 1.
Sigmoid function is commonly used in machine learning for binary classification problems.
It is defined as f(x) = 1 / (1 + e^(-x)), where e is the base of the natural logarithm.
The output of the sigmoid function is always in the range (0, 1).
It is used to convert a continuous input into a probability value.
Example: f(0) = 0.5
A T-test in logistic regression is used to determine the significance of individual predictor variables.
T-test in logistic regression is used to test the significance of individual coefficients of predictor variables.
It helps in determining whether a particular predictor variable has a significant impact on the outcome variable.
The null hypothesis in a T-test for logistic regression is that the coefficient of the predi...
To fit a model to an unexplored market, conduct thorough market research, gather relevant data, identify key variables, test different models, and continuously iterate and refine the model.
Conduct thorough market research to understand the dynamics of the unexplored market
Gather relevant data on customer behavior, market trends, competition, etc.
Identify key variables that may impact the market and model outcomes
Test d...
I applied via Campus Placement and was interviewed before Dec 2023. There were 2 interview rounds.
The first technical round will cover how computer vision works, including the advantages and disadvantages of regression and random forest. It will also include discussions on when to use precision and recall, methods to reduce false positives, and criteria for selecting different models. Additionally, disadvantages of PCA will be addressed, along with project-related questions. The second round will focus on standard aptitude tests, while the third round will involve a casual conversation with the Executive Vice President.
Normal aptitude questions
I applied via Job Portal and was interviewed in Dec 2021. There were 2 interview rounds.
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3-8 Yrs
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