Python Machine Learning with NLP: Classification Quiz

What are the two most common high level problems that can be solved with machine learning?

• Naïve Bayes and Scikit-learn

• Regression and Clustering

• Classification and Clustering

• Supervised Learning and Unsupervised Learning

What is the main focus of unsupervised machine learning?

• Inferring a function from labeled data

• Predicting values of class attribute

• Describing hidden structure from unlabeled data

• Using both labeled and unlabeled data for training

What is the main problem that can be solved with supervised learning in a healthcare setting?

• Finding out which customers made similar product purchases

• Inventory categorization

• Grouping inventory by sales activity

• Predicting high-risk patients and discriminating them from low-risk patients

What is the main focus of unsupervised machine learning in a business case?

• Predicting high-risk patients and discriminating them from low-risk patients

• Grouping inventory by manufacturing metrics

• Inferring a function from labeled data

• Describing hidden structure from unlabeled data

Which of the following is a machine learning step in the classification process?

• Data Visualization

• Shuffle (Randomize) Data

• Data Pre-processing

• Data Collection

What is an example of a deep learning application in natural language processing?

• Inventory categorization

• Voice Assistant

• Grouping inventory by sales activity

• Predicting high-risk patients and discriminating them from low-risk patients

Which Python package is the fundamental package for scientific computing with Python?

• Scikit-learn

• Scipy

• NLTK

• Numpy

What is the main assumption of Naïve Bayes classification?

• Predictors are independent of each other

• Predictors are unrelated to each other

• Predictors are unrelated to the class

• Predictors are dependent on each other

What is the main focus of the feature extractor in text classification?

• Converting input into a machine learning algorithm

• Converting input into a feature set

• Converting input into a numeric feature

• Converting input into a feature set and labels

What is an example of application of the Naïve Bayes text classification with NLTK?

• Classifying gender based on German names

• Classifying occupation based on French names

• Classifying nationality based on Italian names

• Classifying age based on Korean names