Mahindra Finance
Proud winner of ABECA 2024 - AmbitionBox Employee Choice Awards
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I applied via campus placement at Indian Institute of Technology (IIT), Chennai and was interviewed in Oct 2024. There was 1 interview round.
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Common ways to evaluate Time Series model include AIC, BIC, RMSE, MAE, ACF, PACF, etc.
Use Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) to compare models
Calculate Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE) to assess model accuracy
Analyze Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) to check for autocorrelation in residuals
Use techniques like feature selection, regularization, PCA, and VIF to handle multicollinearity.
Perform feature selection to choose the most relevant variables for the model.
Apply regularization techniques like Lasso or Ridge regression to penalize high coefficients.
Utilize Principal Component Analysis (PCA) to reduce dimensionality and decorrelate variables.
Check for Variance Inflation Factor (VIF) to identify highly
TF IDF is a technique used in NLP to measure the importance of a word in a document within a collection of documents.
TF IDF stands for Term Frequency-Inverse Document Frequency.
It is used to determine how important a word is in a document relative to a collection of documents.
TF IDF is calculated by multiplying the term frequency (TF) of a word in a document by the inverse document frequency (IDF) of the word across al...
Create data frame, make histogram
I was interviewed in Jan 2024.
I applied via Walk-in and was interviewed in Oct 2023. There were 3 interview rounds.
posted on 2 Nov 2024
Data related to finance
posted on 7 Apr 2024
I applied via LinkedIn and was interviewed in Mar 2024. There was 1 interview round.
Tell me about yourself
I applied via Naukri.com
posted on 6 Sep 2021
I applied via Recruitment Consultant and was interviewed in Mar 2021. There were 4 interview rounds.
I am very familiar with Python, SQL, and ML models.
I have extensive experience using Python for data analysis and machine learning tasks.
I am proficient in writing SQL queries to extract data from databases.
I have worked with a variety of ML models, including regression, classification, and clustering.
I am familiar with popular ML libraries such as scikit-learn, TensorFlow, and Keras.
I have experience with data preproc...
ML classification models use various metrics to evaluate performance.
Common metrics include accuracy, precision, recall, F1 score, and AUC-ROC.
Accuracy measures the proportion of correct predictions.
Precision measures the proportion of true positives among all positive predictions.
Recall measures the proportion of true positives among all actual positives.
F1 score is the harmonic mean of precision and recall.
AUC-ROC me...
Outliers can significantly impact analysis. It's important to identify and handle them appropriately.
Visualize the data to identify outliers
Consider the source of the outliers and whether they are valid data points
Remove outliers if they are invalid or use robust statistical methods that are less sensitive to outliers
Document any handling of outliers in the analysis report
The organization used descriptive and inferential statistics to analyze and build models.
Descriptive statistics were used to summarize and describe the data, such as mean, median, and standard deviation.
Inferential statistics were used to make predictions and draw conclusions about the population based on the sample data, such as hypothesis testing and regression analysis.
The organization may have also used time series...
Interview experience
Business Executive
330
salaries
| ₹1 L/yr - ₹5 L/yr |
Area Business Manager
316
salaries
| ₹4 L/yr - ₹15 L/yr |
Deputy Manager
298
salaries
| ₹4 L/yr - ₹12 L/yr |
Collections Executive
297
salaries
| ₹1.4 L/yr - ₹5.2 L/yr |
Assistant Manager
239
salaries
| ₹2.5 L/yr - ₹10 L/yr |
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