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Brane Enterprises
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It contain both Aptitude and Coding about base models and Deep learning too
Different models techniques include linear regression, decision trees, random forests, support vector machines, and neural networks.
Linear regression is used for predicting continuous values.
Decision trees are used for classification and regression tasks.
Random forests are an ensemble method based on decision trees.
Support vector machines are used for classification tasks.
Neural networks are used for complex pattern re
Different performance metrics are used for different types of machine learning models to evaluate their effectiveness.
For classification models, metrics like accuracy, precision, recall, F1 score, and ROC-AUC are commonly used.
For regression models, metrics like mean squared error (MSE), mean absolute error (MAE), and R-squared are commonly used.
For clustering models, metrics like silhouette score and Davies-Bouldin in...
I was interviewed in Oct 2023.
Top trending discussions
I applied via Referral and was interviewed before Jun 2023. There were 4 interview rounds.
Data Science MCQ questions
Building a baseline ML model with EDA etc.
Outliers can be analyzed using statistical methods like Z-score, IQR, or visualization techniques like box plots.
Calculate Z-score and identify data points with Z-score greater than a certain threshold as outliers.
Use Interquartile Range (IQR) to detect outliers by identifying data points outside 1.5 * IQR range.
Visualize data using box plots to identify any data points that fall outside the whiskers.
Consider domain kn...
I applied via Naukri.com and was interviewed before Feb 2023. There were 2 interview rounds.
LSTM is a type of RNN that addresses the vanishing gradient problem by using memory cells.
RNN stands for Recurrent Neural Network, a type of neural network that processes sequential data.
LSTM stands for Long Short-Term Memory, a type of RNN that includes memory cells to retain information over long sequences.
LSTM is designed to overcome the vanishing gradient problem, which occurs when training RNNs on long sequences.
L...
Evaluation matrices are used to assess the performance of models in data science.
Confusion matrix: used to evaluate the performance of classification models.
Precision, recall, and F1 score: measures for binary classification models.
Mean squared error (MSE): evaluates the performance of regression models.
R-squared: assesses the goodness of fit for regression models.
Area under the ROC curve (AUC-ROC): evaluates the perfo...
posted on 29 Nov 2024
I applied via Naukri.com and was interviewed before Nov 2023. There were 4 interview rounds.
Developed a machine learning model to predict customer churn for a telecom company.
Collected and cleaned customer data including usage patterns and demographics
Used classification algorithms like Random Forest and Logistic Regression to build the model
Evaluated model performance using metrics like accuracy, precision, and recall
Math, English, reasoning
I applied via Naukri.com and was interviewed before Jan 2024. There was 1 interview round.
I am a data scientist with a background in statistics and machine learning.
Background in statistics and machine learning
Experience with data analysis and visualization tools like Python, R, and Tableau
Strong problem-solving skills
Ability to communicate complex technical concepts to non-technical stakeholders
Developed a predictive model for customer churn in a telecom company using machine learning algorithms.
Used Python for data preprocessing and model building
Implemented algorithms like Random Forest and Logistic Regression
Evaluated model performance using metrics like accuracy and AUC-ROC curve
Handling critical situations requires quick thinking, clear communication, and a calm demeanor.
Assess the situation and prioritize actions
Communicate clearly and effectively with all parties involved
Remain calm and focused
Take decisive action while considering potential consequences
Seek assistance or advice from colleagues or superiors if necessary
I prioritize the problems based on urgency and importance, and then allocate time and resources accordingly.
Assess the urgency and importance of each problem
Create a plan of action for each problem
Allocate time and resources based on the plan
Regularly reassess and adjust the plan as needed
Example: If one problem is a deadline that cannot be missed and the other is a minor issue, prioritize the deadline and allocate mor
I applied via Referral and was interviewed before Aug 2022. There were 3 interview rounds.
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