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IAPP301 EXAM 02
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IAPP301 EXAM 02

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Questions and Answers

Match the Python keyword with its purpose.

Allows a loop to be stopped completely = break Simply acts as a placeholder. = pass

  • = - Allows a loop to stop the current iteration of a loop and continue with the next one. = continue

Match the mathematics function from the math module with its description.

Rounds a value down to the closest integer, but returns a float. = math.floor() Rounds a value up to the closest integer, but returns a float. = math.ceil() Receives two values. Raises the first value to the power of the second value. Returns the result as a float. = math.pow() n/a = n/a

Match the format character with what it represents.

floating-point = f floating-point with ? number of floating-point digits = .?f exponent (scientific) notation = e hexadecimal with lowercase letters = x

Match the description of the file mode to its designation.

<p>A writable file which may also be read from. = w+ A readable file. = r A readable file which may also be written to = r+ A file to which extra content may be added = a</p> Signup and view all the answers

Which one of the following is not an object or method in the socket module?

<p>connect_cl()</p> Signup and view all the answers

Which of the following port numbers is not a valid / recommended listening port when working with sockets?

<p>486</p> Signup and view all the answers

Match the machine learning algorithm/type to its description.

<p>Based on Bayes theorem. = Naive Bayes Represents a series of recursive splits of the independent variables. = Decision tree n/a = n/a Tries to find the best separating line between the features. = Support vector</p> Signup and view all the answers

Match the machine learning algorithm/type to its description.

<p>Classifies a data set by creating a series of clusters = K-Means Consists of a collection of decision trees = Random forest Assumes a linear relationship between input variables and the single output. = Linear n/a = n/a</p> Signup and view all the answers

Study Notes

Python Keywords

  • Keywords are reserved words in Python that have a special meaning, defining the syntax structure of code.
  • They include control flow statements (e.g., if, for), data type definitions (e.g., int, str), and function definitions (e.g., def, return).

Mathematics Functions in Math Module

  • The math module provides mathematical functions such as:
    • sqrt(x): Returns the square root of x.
    • pow(x, y): Returns x raised to the power of y.
    • factorial(n): Returns the factorial of an integer n.
    • sin(x), cos(x), tan(x): Return the sine, cosine, and tangent of x (in radians).

Format Characters

  • Format characters in Python are used for string formatting:
    • %d: Represents integer values.
    • %f: Represents floating-point numbers.
    • %s: Represents string values.
    • %x: Represents integers in hexadecimal format.

File Modes in Python

  • File modes dictate how a file is accessed:
    • r: Read mode; opens a file for reading (default).
    • w: Write mode; opens a file for writing (overwrites existing files).
    • a: Append mode; opens a file for appending new data.
    • rb, wb, ab: Binary modes for reading, writing, and appending, respectively.

Socket Module

  • The socket module provides low-level networking interfaces:
    • Common objects include socket(), bind(), listen(), and accept().
    • Typical methods include connect(), send(), and recv().

Listening Ports

  • Valid listening ports are typically within the range of 1024-49151 for user applications.
  • Common reserved ports include well-known services (e.g., 80 for HTTP, 443 for HTTPS).

Machine Learning Algorithms

  • Common types of machine learning algorithms include:
    • Supervised Learning: Involves training on labeled data to predict outcomes.
    • Unsupervised Learning: Involves identifying patterns in unlabeled data.
    • Reinforcement Learning: Involves agents that learn optimal actions through trial and error.

General Knowledge

  • Recognize popular libraries for machine learning such as TensorFlow and Scikit-learn, which provide tools for different types of algorithms and applications.

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