Review of Python Intro to AI and Data Science

A comprehensive set of flashcards covering key vocabulary and concepts from the Python Intro to AI and Data Science lecture.

Python

A popular structured and object-oriented programming language used in various domains including AI and Data Science.

Compiler

A program that translates the entire source code into machine code at once, creating an executable.

Interpreter

A program that translates source code line by line during runtime.

Data Type

The classification of data into specific types, such as integers, floats, strings, etc.

List

A mutable sequence type in Python that allows duplicate values and is indexed.

Tuple

An immutable sequence type that cannot change after creation and allows duplicate values.

Dictionary

A mutable mapping type that stores key-value pairs, allowing fast access to values based on keys.

Set

An unordered collection type that does not allow duplicate values and is mutable.

Machine Language

The lowest-level programming language consisting of binary code understood directly by a computer.

Assembly Language

A low-level language that uses symbolic representations to represent machine-level instructions.

High-level Language

A programming language that enables abstraction and is closer to human languages.

OOP (Object-Oriented Programming)

A programming paradigm based on the concept of 'objects' which can contain data and code.

Function

A block of reusable code that performs a specific task and can take parameters and return values.

Input Function

A function used to take input from the user, returning it as a string.

Print Function

A built-in function in Python that outputs data to the console.

Boolean

A data type that can hold one of two values: True or False.

Loop

A programming construct that repeats a block of code as long as a specified condition is true.

Numpy

A popular open-source library in Python for numerical computations, providing support for arrays and matrices.

Library

A collection of pre-written code that extends the capabilities of programming languages.

Math Module

A built-in library in Python that provides various mathematical functions.

Comparison Operators

Operators used to compare values, such as

Algorithm

A step-by-step procedure or formula for solving a problem.

Array

A collection of items stored at contiguous memory locations.

Matrix

A two-dimensional array used in linear algebra.

Variable

A storage location identified by a variable name that can hold data.

Identity Operator

Operators that determine whether two references point to the same object in memory.

Membership Operator

Operators used to test if a value is found in a sequence, such as 'in' and 'not in'.

Slicing

An operation that enables selecting a portion of a sequence by specifying a start and end index.

Lambda Function

An anonymous function defined by the lambda keyword, often used for short functions.

Exception Handling

A programming construct that handles errors or exceptions gracefully.

Debugging

The process of identifying and fixing bugs or errors in code.

Inheritance

A mechanism in OOP where one class can inherit attributes and methods from another class.

Polymorphism

A feature in OOP that allows methods to do different things based on the object it is acting upon.

Encapsulation

The bundling of data and methods that operate on that data within a single unit or class.

Recursion

The process in which a function calls itself directly or indirectly.

Commenting in Code

Adding notes in code for clarity, which are ignored by the interpreter.

String Concatenation

Combining two or more strings into one.

Function Call

The execution of a function in program code.

Conditional Statement

A feature that performs different actions based on whether a specified condition evaluates to true or false.

Debugging Tools

Tools or techniques used for analyzing code to find and fix bugs.

Scope of Variables

The context in which a variable is defined and accessible.

Global Variable

A variable declared outside of any function, making it accessible from any function.

Local Variable

A variable declared within a function, only accessible within that function.

Method

A function that is associated with an object and can access its attributes.

Array Indexing

Using indices to access elements of an array.

Multidimensional Array

An array that has more than one dimension, such as a two-dimensional array.

List Comprehension

A concise way to create lists in Python by iterating over an iterable.

Parameter

A variable in a function definition that accepts values passed to the function.

Argument

The actual value that is passed to a function when it is called.

Return Statement

A statement used to exit a function and return a value.

Data Structure

A way of organizing and storing data in a computer so it can be accessed and modified efficiently.

Stack

A data structure that follows the Last In First Out (LIFO) principle.

Queue

A data structure that follows the First In First Out (FIFO) principle.

Hash Table

A data structure that implements an associative array, a structure that can map keys to values.

Simulation

The imitation of a real-world process or system over time.

Analysis

The detailed examination of the elements or structure of something.

Visualization

The technique of creating images, diagrams, or animations to represent data.

Artificial Intelligence

The simulation of human intelligence processes by machines, especially computer systems.

Machine Learning

A subset of AI that enables systems to learn from data instead of being explicitly programmed.

Deep Learning

A class of machine learning based on artificial neural networks.

Overfitting

A modeling error that occurs when a model learns the noise in the training data rather than the actual distribution.

Underfitting

A modeling error that occurs when a model is too simple to capture the underlying trend of the data.

Classification

A supervised learning task of predicting the class or category of an input data point.

Regression

A statistical method used to predict continuous outcomes.

Clustering

An unsupervised learning method used to group similar data points together.

Feature Engineering

The process of using domain knowledge to create features that make machine learning algorithms work.

Training Data

The dataset used to train a model.

Test Data

The dataset used to evaluate the performance of a trained model.

Validation Set

A subset of the dataset used to provide an unbiased evaluation of a model fit on the training dataset.

Hyperparameter Tuning

The process of optimizing the parameters that govern the learning process.

Cross-Validation

A technique for assessing how the results of a statistical analysis will generalize to an independent dataset.

Normal Distribution

A probability distribution that is symmetric about the mean, showing that data near the mean are more frequent.

Variance

A measure of how far a set of numbers are spread out from their average value.

Bias

The systematic error introduced by approximating a real-world problem.

Outlier

An observation point that is distant from other observations.

Dataset

A collection of data, usually presented in tabular form.

Data Wrangling

The process of cleaning and transforming raw data into a format suitable for analysis.

Big Data

Extremely large datasets that may be analyzed computationally to reveal patterns, trends, and associations.

Data Mining

The process of discovering patterns in large data sets.

Feature Selection

The process of selecting a subset of relevant features for model construction.

Dimensionality Reduction

Techniques used to reduce the number of input variables in a dataset.

Support Vector Machine (SVM)

A supervised machine learning algorithm that can be used for classification or regression challenges.

Neural Network

A series of algorithms that attempt to recognize underlying relationships in a set of data.

Random Forest

An ensemble learning method for classification, regression, and other tasks that operates by constructing multiple decision trees.

Decision Tree

A model that uses a tree-like graph to make decisions based on features.

Ensemble Learning

A method that combines multiple learning algorithms to achieve better predictive performance.

Gradient Boosting

A machine learning technique for regression and classification problems, which builds a model in a stage-wise fashion from additive models.

K-Nearest Neighbors (KNN)

A simple, instance-based learning algorithm used for classification.

A/B Testing

A method of comparing two versions of a webpage to see which one performs better.

Web Scraping

The process of automatically extracting information from websites.