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Introduction to Machine Learning, Exams of Nursing

Chamberlain College of Nursing Nursing

An overview of the fundamental concepts in machine learning, including the three main types of learning (unsupervised, reinforcement, and supervised), the differences between training and testing data, and the concepts of hypotheses and their role in supervised learning. It also covers the differences between classification and regression tasks, as well as the key differences between numpy arrays and python lists. The document also explains the purpose and usage of various numpy functions, such as reshape(), vstack(), and hstack(), as well as the colon splicing operator. Additionally, it outlines the purposes of popular python libraries like numpy, scipy, scikit-learn, and matplotlib, which are widely used in the field of machine learning and data analysis.

Typology: Exams

2024/2025

Available from 09/20/2024

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1.4K documents

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Download Introduction to Machine Learning and more Exams Nursing in PDF only on Docsity! Intro to Machine Learning What are two reasons why we want to incorporate learning into an agent-based system? - ANS>1) Agent to solve task without exactly knowing all the scenarios that it will find itself in 2) Agent that can solve task but in the future are wanting to have it make predictions of the system (Stock market) What are the three types of learning? - ANS>1) Unsupervised Learning: Learns patterns in the input even though no explicit feedback is supplied 2) Reinforcement Learning: The agent learns from a series of reinforcements - rewards or punishments 3) Supervised Learning: Agent observes some example input-output pairs and learns a function that maps from input to output. Explain the difference between training data and testing data. - ANS>Training data is a subsect of the entire data set that is used to train an agent to find a hypothesis function that is then tested on a testing data set, which is the remainder of the data set. What is a hypothesis in the context of supervised learning? - ANS>A function that is found by the agent given a data set it is told to analyze. This is what is then put to the test by applying the hypothesis to a testing data set. What is the difference between classification and regression? - ANS>Classification is whenever the output value, y, is one of a finite set of values. Regression is when a real number (near-infinite possibilities) is the output value of the function. What is the difference between a NumPy array and a Python list regarding the data types of the arrays and lists? - ANS>NumPy arrays must contain elements of the same type or have a common supertype in common. NumPy will automatically adjust the typing so that the elements can be accommodated, much like an object-oriented programming language (for example, Java with the use of generic, all the elements must have a common link in order to be paired together in the array). Python lists will contain any value you pass in. How would you create a NumPy array with 5 rows and 10 cdolumns, and all elements have a value of 0? - ANS>arr = np.zeros((5,10))