Dictionary‐matching algorithm that locates elements of a finite set of strings (the “dictionary”) within an input text and attempts to match all strings simultaneously.
Ex. 4.20.
Boyer and Moore
An efficient string‐searching algorithm that is the standard benchmark for practical string‐search literature.
Alg 3.4
Knuth, Pratt, and Morris
Algorithm, which checks the characters from left to right, and when a pattern has a sub‐pattern that appears more than one in the sub‐pattern, it uses that property to improve the time complexity.
Alg 3.2
Naïve (brute force)
Very general problem‐solving technique and algorithmic paradigm that consists of systematically enumerating all possible candidates for the solution and checking whether each candidate satisfies the problem's statement.
Alg 3.1
Rabin and Karp
A string‐searching algorithm that uses hashing to find patterns in strings.
Alg 3.3.
AI, ML, and Data Science Artificialintelligence(AI)
Interdisciplinary field, usually regarded as a branch of computer science, dealing with models and systems for the performance of functions generally associated with human intelligence, such as reasoning and learning.
1.5.2.
Fuzzy logic
Form of logic, which is much closer to human thinking logic and a natural language than traditional binary logic.
1.5.6, 5.2.4
Expert systems
Intelligent computer program that uses knowledge and inference procedures to solve problems that are difficult enough to require significant human expertise for their solution.
1.5.5, 2.5, 5.2.4
Knowledge‐based
A knowledge‐based system is a computer program that reasons and uses a knowledge base to solve complex problems.
1.5.5, 2.5
Ex. 3.1
Artificial neural networks
A computing system, made up of a number of simple, highly interconnected processing elements, which processes information by its dynamic state response to external inputs.
1.5.8, 3.6.5
Autoencoders
The model that aims to reconstruct data from the input layer into the output layer with a minimal amount of distortion.
Backpropagation
Shorthand for “backward propagation of errors,” is a method of training ANN where the system’s initial output is compared to the desired output, then adjusted until the difference (between outputs) becomes minimal.
1.5.8
Convolutional
Multilayer topology with a few hidden layers, where each neuron receives its input only from a subset of neurons of the previous layer.
1.5.8, 5.4.2, 6.5.2
Ex.5.8
Deep belief
Composition of Restricted Boltzmann Machines (RBM), a class of neural networks with no output layer.
1.5.8
Generative adversarial networks (GAN)
Unsupervised learning technique that is capable to generate data with selected properties similar to a dataset of our choice.
6.5
Long Short Term Memory
Special type of recurrent topology, which has memory cells that maintain information in memory for a longer period.
5.1.8.3
Multilayer perceptron (MLP)
An ANN model, in which neurons compose a layer and layers are connected between each other creating an ANN with certain connectivity organization rules to follow up.
ANN topology that consists of multiple time‐based MLPs, all connected to a single‐end MLP, with time series used as inputs.
3.6.5.3, 4.6.3
Ex. 4.22
Radial basis function (RBF)
ANN that uses radial basis functions as activation functions, producing an output, which is a linear combination of radial basis functions of the inputs and neuron parameters.
3.6.5.3
Recurrent
A multilayer topology, which includes the feedback loop that connects its output to the inputs.
1.5.8, 5.1.8.3
Data science
The field that combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data.
Conventional Techniques
