Elective III - Machine Learning Reviewer
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Questions and Answers

What is the primary measure of success in resource management?

  • Inputs multiplied by outputs
  • Outputs divided by inputs (correct)
  • Outputs plus inputs
  • Inputs minus outputs

    • Which of the following is NOT one of Mintzberg's managerial roles?

  • Spokesperson
  • Leader
  • Analyzer (correct)
  • Entrepreneur

    • What is the first step in the decision-making process for managers?

  • Define the problem (correct)
  • Evaluate possible solutions
  • Construct a model
  • Compare and recommend a solution

    • In the context of decision-making, what type of decisions are classified as semi-structured?

    <p>Decisions that require both analyzed data and human judgment</p> Signup and view all the answers

    Which characteristic does a Decision Support System (DSS) primarily provide?

    <p>Integration of human intellect with computing power</p> Signup and view all the answers

    What primary goal does supervised learning aim to achieve?

    <p>Create outputs from known inputs with assigned desired outputs</p> Signup and view all the answers

    Which of the following is an example of supervised learning?

    <p>Detecting fraudulent credit card transactions</p> Signup and view all the answers

    What distinguishes unsupervised learning from supervised learning?

    <p>Supervised learning requires user-defined outputs while unsupervised does not</p> Signup and view all the answers

    Which library is primarily used for scientific plotting in Python within machine learning?

    <p>matplotlib</p> Signup and view all the answers

    In which scenario would supervised learning be applicable?

    <p>Predicting whether a tumor is benign or malignant based on diagnostics</p> Signup and view all the answers

    What type of machine learning task is involved in determining a zip code from handwritten digits?

    <p>Classification task</p> Signup and view all the answers

    What is a characteristic of classification tasks in supervised learning?

    <p>The goal is to categorize outputs into predefined classes</p> Signup and view all the answers

    Which library would be most suitable for handling multidimensional arrays in machine learning?

    <p>Numpy</p> Signup and view all the answers

    What is the primary objective of Business Intelligence (BI)?

    <p>To enable easy access to data for analysis</p> Signup and view all the answers

    Which of the following correctly identifies a component of a BI system?

    <p>Data warehouse for source data</p> Signup and view all the answers

    Which evolution of BI includes capabilities for AI and data mining?

    <p>The inclusion of AI and data/text mining capabilities in the 2010s</p> Signup and view all the answers

    What characterization best describes Business Intelligence in terms of its definition?

    <p>An umbrella term combining various components for data analysis</p> Signup and view all the answers

    Which form of analytics focuses on predicting future outcomes based on historical data?

    <p>Predictive Analytics</p> Signup and view all the answers

    What is a key characteristic of a model that generalizes well?

    <p>It accurately predicts outcomes for unseen data.</p> Signup and view all the answers

    Which of the following best describes overfitting?

    <p>The model closely fits training data but fails on new data.</p> Signup and view all the answers

    What is the purpose of data normalization?

    <p>To ensure all values are scaled to a range between 0 and 1.</p> Signup and view all the answers

    In the context of managerial decision making, which response is most proactive?

    <p>Employing strategic planning and innovative business models.</p> Signup and view all the answers

    What is label encoding used for in data preprocessing?

    <p>To convert categorical data into numerical form.</p> Signup and view all the answers

    What is the impact of globalization on the business environment?

    <p>It introduces new complexities and opportunities.</p> Signup and view all the answers

    What is the goal of regression tasks in data analysis?

    <p>To predict a continuous outcome variable.</p> Signup and view all the answers

    What is the primary aim of a business's response to competitive pressures?

    <p>To facilitate operational efficiency and effectiveness.</p> Signup and view all the answers

    Study Notes

    Introduction to Machine Learning

    • Machine learning (ML) focuses on extracting knowledge from data through research fields like statistics, artificial intelligence, and computer science.
    • Early ML applications relied on simple rule-based "if" and "else" decisions.
    • The main goal is to automate decision-making processes effectively.

    Types of Machine Learning

    • Supervised Learning

      • Involves user-provided pairs of inputs and desired outputs.
      • Can generate outputs for unseen inputs without human assistance.
      • Example: Spam classification.

    • Unsupervised Learning

      • Deals only with input data, lacking predefined output labels.
      • Typically more challenging to understand and evaluate.
      • Examples include text data analysis, customer segmentation, and anomaly detection.

    Essential Libraries for Machine Learning

    • Scikit-learn: Offers a variety of machine learning algorithms.
    • Numpy: Handles multidimensional arrays and basic linear algebra.
    • SciPy: Provides advanced mathematical functions, optimization, and statistical operations.
    • Matplotlib: A primary library for scientific plotting, supports high-quality visualizations.
    • Pandas: Focused on data wrangling and analysis, organized around the DataFrame structure.

    Types of Supervised Machine Learning Tasks

    • Classification Tasks

      • Aim to predict a specific class label from defined possibilities (e.g., benign vs. malignant tumors).
      • Binary Classification: Involves distinguishing between two classes.
      • Multiclass Classification: Differentiate among multiple classes.

    • Regression Tasks

      • Predict continuous numerical outputs, such as income based on various factors.

    Generalization, Overfitting, and Underfitting

    • Generalization: The ability of a model to make accurate predictions on new, unseen data.
    • Overfitting: Occurs when a model is too closely fit to training data, leading to poor performance on new data.
    • Underfitting: A model that fails to capture the training data patterns and also lacks generalization ability.

    Data Preprocessing Techniques

    • Normalization: Rescaling data to a range between 0 and 1.
    • Standardization: Centering data around a mean of zero and a standard deviation of one.
    • Label Encoding: Converting categorical labels into numerical format for algorithm compatibility.

    Business Intelligence, Analytics, and Decision Support

    • Organizations are transitioning to computerized support systems to enhance operations and respond to business pressures.
    • The business environment is increasingly complex due to factors like globalization and technology.

    Organizational Responses

    • Organizations should adopt reactive, anticipative, adaptive, and proactive strategies.
    • Strategic planning and innovative business models are vital for success.

    Managerial Decision Making

    • Management involves utilizing resources to achieve organizational goals, emphasizing decision-making.
    • The decision-making process typically follows a structured approach:
      • Define the problem or opportunity.
      • Construct a model for analysis.
      • Identify and evaluate possible solutions.
      • Recommend the best solution.

    Early Decision Support Framework

    • Decisions are categorized by degrees of structuredness:
      • Highly structured, semi-structured, and highly unstructured.
    • Types of managerial control include strategic, management, and operational levels.

    Decision Support Systems (DSS)

    • DSS are interactive systems that combine human intellect with computational capabilities for solving unstructured problems.
    • Business Intelligence (BI) has evolved from these decision support concepts, now emphasizing user-friendly access to data and analysis tools.

    Definition and Evolution of Business Intelligence

    • BI encompasses various architectures, tools, and methodologies aimed at providing decision-makers with easy data access.
    • Key goals include transforming data into actionable insights.
    • The term BI originated in the mid-1990s, evolving from earlier information systems like MIS and EIS.

    Architecture of Business Intelligence

    • A typical BI system consists of:
      • Data Warehouse: Source of consolidated data.
      • Business Analytics: Tools for data manipulation and analysis.
      • Business Performance Management (BPM): For monitoring and performance analysis.
      • User Interface: Facilitates interaction, often via dashboards.

    Analytics Overview

    • Analytics can be categorized into three types:
      • Descriptive Analytics: Analyzes past data.
      • Predictive Analytics: Forecasts future trends based on data.
      • Prescriptive Analytics: Recommends actions based on data analysis.

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    Description

    This quiz reviews key concepts in machine learning, covering its introduction, research fields, and the basics of supervised learning. It focuses on extracting knowledge from data and the role of algorithms in decision-making processes. Perfect for students looking to consolidate their understanding of machine learning fundamentals.

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