Owidi (@owidi-001)
github

owidi-001

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  • Stars
    star
    7
  • Global Rank 1,193,096 (Top 42 %)
  • Followers 8
  • Following 18
  • Registered almost 6 years ago
  • Most used languages
    Dart
         50.0 %
    Python
         33.3 %
    HTML
         16.7 %
  • Location 🇰🇪 Kenya
  • Country Total Rank 2,245
  • Country Ranking
    Dart
         149
    Python
         1,275
    HTML
         1,628

Top repositories

1

Keylogger_-_detector_gui

Computer security key stroke logger and detector program made with tkinter
Python
1
star
2

owidi-001

Config files for my GitHub profile.
1
star
3

NewsFlux

A new application using riverpod. For learning purpose. Consumes some news api that I'll find out later.
Dart
1
star
4

Eucossa-frontend

Web frontend for the Egerton University Computer Science Student Association
HTML
1
star
5

electros_app

An electronic shop with flutter
Dart
1
star
6

delidash-customer

My final year personal project. Is a food store collection app, simulates vendor, customer and rider application.
Dart
1
star
7

Soundex-Algorithm

People can have very similar sounding names that are spelled differently. When hearing a name without knowing the spelling, someone may spell the name in several different ways. We would like a tool that can roughly group similar sounding names together to allow us to search for names when an exact spelling may not be known. Different sounding names can arise for a variety of reasons, including individual preference of parents in assigning first names and differing ways to transliterate names from other languages into the Latin alphabet, for example. There are obvious limitations and biases to approaches to group similar sounding names together: many were originally designed for names that were historically common in the United States, and likely perform better on common Western European names. They will likely not sufficiently capture differences or similarities in names from other backgrounds. Phonetic algorithms are tools used to compare similar sounding names. In this assignment, we will implement a variety of the Soundex algorithm, originally developed and patented in 1918. In the version of Soundex algorithm that we are implementing, each name will be translated into a string of the form AXXX, where A is a lower-case letter and XXX is a three-digit numerical code. We call this string the Soundex encoding of the name. Two names will be judged to be similar sounding if their Soundex encodings are the same. We are choosing the Soundex algorithm for simplicity, as it relies on a relatively small number of rules. However, as an older algorithm, Soundex will likely not perform as well as more modern algorithms on diverse groups of names.
Python
1
star