Ascendion Interview Questions and Answers

Deep learning neural networks are a type of artificial neural network with multiple layers, used for complex pattern recognition.

• Deep learning neural networks consist of multiple layers of interconnected nodes, allowing for more complex patterns to be learned.

• They are capable of automatically learning features from data, eliminating the need for manual feature engineering.

• Examples include Convolutional Neural Networks (CNNs) for image recognition and Recurrent Neural Networks...read more

Biasing is the error due to overly simplistic assumptions in the learning algorithm. Overfitting is when a model is too complex and fits the training data too closely, leading to poor generalization. Underfitting is when a model is too simple to capture the underlying structure of the data.

• Biasing occurs when a model has high error on both training and test data due to oversimplified assumptions.

• Overfitting happens when a model is too complex and captures noise in the trainin...read more

Neural network is a computational model inspired by the way the human brain works, used for machine learning tasks.

• Neural network is a series of algorithms that attempts to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates.

• Backpropagation is a technique used to train neural networks by updating the weights of the network to minimize the difference between the predicted output and the actual output.

• CNN (Convoluti...read more

Precision is the ratio of correctly predicted positive observations to the total predicted positives, while recall is the ratio of correctly predicted positive observations to the all observations in actual class.

• Precision focuses on the accuracy of positive predictions, while recall focuses on the proportion of actual positives that were correctly identified.

• Precision = TP / (TP + FP), Recall = TP / (TP + FN)

• High precision means that when the model predicts a positive result...read more

I am looking for a competitive salary based on industry standards and my experience.

• Research industry standards for Data Scientist salaries

• Consider my level of experience and skills when determining salary expectations

• Be open to negotiation based on the overall compensation package offered

Stemming and lemmatization are techniques used in natural language processing to reduce words to their base or root form.

• Stemming is a process of reducing words to their base form by removing suffixes.

• Lemmatization is a process of reducing words to their base form by considering the context and part of speech.

• Stemming is faster but may not always produce a valid word, while lemmatization is slower but produces valid words.

• Example of stemming: 'running' -> 'run', 'jumps' -> 'j...read more

Multicollinearity can be measured using correlation matrix, variance inflation factor (VIF), or eigenvalues.

• Calculate the correlation matrix to identify highly correlated variables.

• Use the variance inflation factor (VIF) to quantify the extent of multicollinearity.

• Check for high eigenvalues in the correlation matrix, indicating multicollinearity.

• Consider using dimensionality reduction techniques like principal component analysis (PCA) to address multicollinearity.