Senior Data Science Consultant Interview Questions and Answers

CNN is preferred over feed forward neural networks due to their ability to capture spatial and temporal dependencies in data.

• CNNs are designed to effectively capture spatial relationships in data, making them ideal for tasks like image recognition.

• CNNs use shared weights and local connectivity to efficiently learn patterns in data, reducing the number of parameters compared to feed forward neural networks.

• CNNs are also capable of capturing temporal dependencies in sequential ...read more

Overfitting occurs when a model learns noise in the training data rather than the underlying pattern, while underfitting occurs when a model is too simple to capture the underlying pattern.

• Overfitting: Model performs well on training data but poorly on unseen data. Can be avoided by using techniques like cross-validation, regularization, and early stopping.

• Underfitting: Model is too simple to capture the underlying pattern. Can be avoided by using more complex models, increas...read more

Cross validation is a technique used to assess the performance of a predictive model by splitting the data into training and testing sets multiple times.

• Divide the data into k subsets (folds)

• Train the model on k-1 folds and test on the remaining fold

• Repeat this process k times, each time using a different fold as the test set

• Calculate the average performance metric across all k iterations to evaluate the model

Customer segmentation methods include demographic, behavioral, psychographic, and geographic segmentation.

• Demographic segmentation: dividing customers based on age, gender, income, education, etc.

• Behavioral segmentation: categorizing customers based on their behavior towards products or services.

• Psychographic segmentation: grouping customers based on their lifestyle, values, beliefs, and personality.

• Geographic segmentation: segmenting customers based on their location, such a...read more