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statements of facts and rules together with a mechanism for setting goals in the form of a query.
Declarative programming
feature of object-oriented programming that allows methods to be redefined for derived classes
Polymorphism
– process in which the methods and data from one class, a superclass or base
Inheritance
An occurrence of an object during the execution of a program.
Instance
an instance of a class that is self-contained and includes data and methods.
Object
– a template defining the methods and data of a certain type of object.
Class
process of putting data and methods together as a single unit, a class.
Encapsulation
– a programming methodology that uses selfcontained objects, which contain programming statements (methods) and data, and which communicate with each other.
OOP
programming paradigm in which the steps required to execute a program are set out in the order they need to be carried out.
Imperative Programming
programming instructions that use the computer’s basic instruction set.
Low-level programming
– a process using a function or procedure that is defined in terms of itself and calls itself.
Recursion
time complexity of binary search
O(logN)
Time complexity of bubble, insertion sort
O(N^2)
Time complexity of a linear search
O(N)
– a mathematical notation used to describe the performance or complexity of an algorithm
Big O notation
a hierarchical data structure in which each parent node can have a maximum of two child nodes.
Binary Tree
a method of sorting data in an array into alphabetical or numerical order by placing each item in turn in the correct position in the sorted list.
Insertion Sort
... - a method of searching an ordered list by testing the value of the middle item in the list and rejecting the half of the list that does not contain the required value.
Binary Search
Statistical measure used to make predictions from data by finding learning relationships between the inputs and outputs.
Regression
Method used in artificial neural networks to calculate error gradients so that actual node/neuron weightings can be adjusted to improve the performance of the model.
Back Propogation
Networks of interconnected nodes based on the interconnections between neurons in the human brain. The system is able to think like a human using these neural networks, and its performance improves with more data.
Artificial Neural Networks
System which is given no training – learns on basis of ‘reward and punishment’.
Reinforcement Learning
System which is able to identify hidden patterns from input data – the system is not trained on the ‘right’ answer
Unsupervised learning
System which is able to predict future outcomes based on past data. It requires both input and output values to be used in the training process.
Supervised Learning
Systems that learn without being programmed to learn.
Machine Learning
Machines that think in a way similar to the human brain. They handle huge amounts of data using artificial neural networks.
Deep Learning
Describe A* algorithm
A* algorithm – an algorithm that finds the shortest route between nodes or vertices but uses an additional heuristic approach to achieve better performance than
Describe Dijkstra’s algorithm
Dijkstra’s algorithm – an algorithm that finds the shortest path between two nodes or vertices in a graph/network.
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