I apologize for any videos that are poor quality, or commentary that is out of context. These videos were
recorded to either send to clients to update them on the progress of their project, or to send to friends
to show off personal projects of my own. Please feel free to contact me for further details on any of the
projects below!
Additionally, these are just a handful of projects I have created. Please keep in mind, in order to protect
my intellectual property, these are neither my most recent, nor my most impressive projects.
Onomono
This is a web application written in a PHP framework called Symfony, which is used to track
users' behavior on websites. In production, this would be done by a remote JavaScript file
which you would include on your website. However, for testing purposes I have the script being
injected via Chrome Extension. Please keep in mind that this is very much an alpha version of the
software.
PHP,JavaScript,Web Socket,Symfony
Voice Recognition
This is a web application written in PHP, NodeJS, and JavaScript that enables voice commands
through a web interface. It utilizes Microsoft Azure's Cognitive Services SDK to convert
spoken words into text, and to also identify user's by their voice. Additionally, Azure is utilized
to return the text response of a command in an audio format as well. The project also uses a weather API
in order to output the weather of either a predefined location, or a zip code given in the voice
command. Lastly, Spotify's API is used to play music on the user's local computer, and any device
linked to the user's Spotify account. The application showcases the addition of a spectrogram
at the bottom of the page to show feedback to the user on the input of their microphone.
PHP,NodeJS,JavaScript,Voice Recognition,Spectrogram,Speech-to-Text,Text-to-Speech,Microsoft Azure,
Spotify API,Web
Apache Log Visualizer
This is a Flask application that uses Scala and PySpark (a Python module for Apache Spark) to aggregate data from apache log files
and display it visually in graphs. It also uses MaxMind's GeoIP2 database to determine the
location of users visiting the site. Some of the more appealing data consists of user's browser
and operating system, traffic referral sources, and the time and day of visits to the site.
Python,Flask,PySpark,Scala,Data Aggregation,Data Visualization,Apache,Web
Social Media Onboarding Platform
To put the contents of this video simply, it is an Onboarding Platform for marketing companies.
I spent many years as a developer consultant at a marketing firm. I noticed that any time
they were bringing on a new client, they would exchange social media credentials in plain text
over email. Naturally, I was appalled, and created this demonstration. How it works:
The marketing company creates a client in the platform.
The client receives an email that will link them to each social network, and let the client
choose the pages that want to grant the marketing company access to.
Using the social media's own API, the onboarding platform retrieves an access token that will
be stored by the onboarding platform. This token can be revoked by the client at anytime.
The marketing company then would be able to post on the client's behalf, no exchange of
passwords required.
The application itself is built in a MVC framework for PHP called Symfony.
PHP,Symfony,Marketing,Twitter API,Facebook API,Instagram API,Email,Social Networking,Onboarding,
Web
Phone Call Lead to Sales Conversation Visualizer
This was a project for a mechanic client with multiple locations. The project pulled data from two sources.
The first source is CallRail, which is a service that gives you different phone numbers to post on your
Facebook/Google Listing/Website, etc. in order to track the source of leads. The second source is
the client's point-of-sale servers from their 5 different store locations. To optimize security,
I connected to each server through a VPN, so I would not have to open any ports to the public,
and downloaded sales logs to a centralized server. The purpose of the project was to match call
records from CallRail with transaction records from the point-of-sale servers in order to determine
how much revenue was being generated by each advertising medium. The project was programmed in Python,
using the Flask framework. Data was stored in MongoDB and was aggregated using Mongo's Pipelines.
The aggregated data is then displayed visually to the client in graphs. Additionally, the data can be further
filtered by dates, store location, and advertising source.
Python,Flask,CallRail API,Point-of-Sales,Server,MSSQL,Networking,MongoDB,Data Aggregation,Data Visualization,
Mongo Pipeline,Web
GUI Application Builder
This is an application builder that allows you to build the pages of the site as well, as control the flow of data
through a custom interface. The site can be programmed without typing a single line of code, simply through
the drag and drop Flow Builder. The structure of the builder is meant to closely follow an MVC structure.
The application can be exported to web, desktop, or mobile with one click. This program itself is
built in a MVC framework for PHP called Symfony.
PHP,Symfony,Builder,Drag and Drop,Web
Real-time Collaboration IDE
This project uses a websocket to deliver a real-time collaborative IDE. This means two or more people
could be making changes to a file, and be able to see the changes made by each other in real time. It
is a fully function IDE with color-coding and emmit installed.
PHP,Websocket,IDE,Web