morgan's Projects
clarity is a POC - the first healthcare prevention software that allows for physicians and insurance providers to see what their patients consume in real-time.
communication networks, network traffic, network impairments, standards, layered reference models for organizing network functions/
Basics of Compilers in relationship to C++ compilation to object and machine code via makefile scripting. Basics of Algorithmic Design - Essentially how to design a sequence of precise instructions that leads to a solution. Principles of object-oriented programming design
Performed base file system operations from the Linux Command Line Enviroment when implementing programs. Derived and employed basic algoritms from given problems Demonstrated basic programming concepts and constructs such as for/while/do-while loops, primative data types i.e. long, short, int, double, strings, char, arrays, pointers, variables, function scope, general debugging techniques, structures, classes, compliation and makefile techniques. Basic functionalities of git
mathmatical implementation of rsa encryption
the core topics to be covered include data preproprocessing, classification, cluster analysis, association analysis, anomaly detection, neural networks, model evaluation, and applications like recommernder systems.
The repo abstract data structures and algorithmic design making use of these structures. Topics include asymptotic analysis, trees, dictionaries, heaps, disjoint set structures; divide and conquer, greedy, and dynamic programming algorithms
Digital Logic Design using VHDL All material in this repo will cover the VHDL and CAD tools. Additional topics will include Boolean algebra, combinational logic circuits, minimization techniques, AND, OR, NOT, NAND, NOR gates, implementation of sequential circuits, and synthesis techniques of logic circuits using VHDL. The following will contain gates and digital systems such as a simple processor.
A donut-shaped C code that outputs a 3D spinning donut
EECS 268 Programming II at The University of Kansas
This repo will illustrate material pertaining to the course embedded systems: an intelligent system with special-purpose computation capabilities. By addressing the internal organization of micro-controller systems used in a variety of engineered systems.
A web application that would provide a public, accessible resource that helps educate consumers about the brands they support so they can make well-informed, more ethical decisions.
VOID
This repo contains general concepts such search procedures, two-person games, predicate calculus and automated theorem proving, nonmonotonic logic, probabilistic reasoning, rule based systems, semantic networks, frames, dynamic memory, planning, machine learning, natural language understanding, neural networks.
The goal of this repo is to document my autodidactic learning of the JavaScript language definitely.
Renamed this fork to learn about it's architecture
this will be a collection of notes and command listings for learning the unix operating system.
This interactive project is intended to teach those who are interested in machine learning about various popular methods.
N/a des for now
UCLANesl - NIST Differential Privacy Challenge (Match 3)
Concepts of object-oriented programming. Covers data abstractions, classes and objects, methods, inheritance, polymorphism, dynamically-bound method calls and data encapsulation.
This program will generator a pseudo randomally generated password based on user set criteria. The following outputs will comprise of ASCII standard value character set, with which the user's password will derive from.
Probability and Stochastic Processes - probability and statistics with applications. Reliability of systems. Discrete and continuous random variables. Expectations, functions of random variables, and linear regression. Sampling distributions, confidence intervals, and hypothesis testing. Joint, marginal, and conditional distribution and densities.
asic concepts and methods in probability and statistics such as sample space, discrete and continuous random variables, probability distributions; introduction to the statistical inference, classical estimation and testing procedures for one and two sample problems; chi-square test.