Name some evaluation metrics? What is precision and recall? Give some examples. What is Entropy and Gini impurity What are bagging techniques What are boosting techniques Difference between validation and test data What is LSTM and GRU Explain K means clustering How to import CSV dataset

Question

Accepted Answer

Explanation of evaluation metrics, precision, recall, entropy, Gini impurity, bagging, boosting, validation vs test data, LSTM, GRU, K-means clustering, and importing CSV datasets.

Evaluation metrics: used to measure the performance of machine learning models (e.g., accuracy, precision, recall, F1 score)
Precision: ratio of true positive predictions to the total predicted positives (TP / (TP + FP))
Recall: ratio of true positive predictions to the total actual positives (TP / (TP + FN))
Entropy: measure of impurity in a set of examples (lower entropy indicates more purity)
Gini impurity: measure of how often a randomly chosen element would be incorrectly classified (lower Gini impurity indicates more purity)
Bagging techniques: ensemble learning method that builds multiple models independently and then combines them (e.g., Random Forest)
Boosting techniques: ensemble learning method that builds models sequentially, each correcting the errors of its predecessor (e.g., AdaBoost)
Validation data: used to tune hyperparameters and evaluate model performance during training
Test data: used to evaluate the final model performance after training
LSTM (Long Short-Term Memory): type of recurrent neural network architecture designed to capture long-term dependencies
GRU (Gated Recurrent Unit): type of recurrent neural network architecture similar to LSTM but with fewer parameters
K-means clustering: unsupervised machine learning algorithm that partitions data into K clusters based on similarity
Importing CSV dataset: use libraries like pandas in Python to read CSV files into dataframes

Name some evaluation metrics? What is precision and recall? Give some examples. What is Entropy and Gini impurity What are bagging techniques What are boosting techniques Difference between validation and test data What is LSTM and GRU Explain K means clustering How to import CSV dataset

Quantiphi Analytics Solutions Private Limited Machine Learning Engineer interview questions & answers

Popular interview questions of Machine Learning Engineer