Skip to content

AlexPatrie/spaceBearAmadeus

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

9 Commits
 
 
 
 

Repository files navigation

  • 👋 Hi, I’m Alex aka spaceBearAmadeus!

  • 👀 I am a classical vocalist, guitarist, pianist, and teacher turned Dev who is humbly seeking to learn as much as possible. I have recently realized that my skills as a classical musician are exactly the same skills that I can tap into as a computer scientist. As a musician, I have always been fascinated by the power of structure and organization to create something truly beautiful. This fascination has translated seamlessly into my passion for software engineering and computer science. I am coming from the field of education and my goal is to transition into an IT career on a full-time basis. Just as reading sheet music allows a musician to understand and recreate a piece of music, reading and writing code allows me to bring structure and organization to large datasets and create solutions that have the potential to impact and improve people's lives.

  • 🧠 My IT background includes network configuration, logging, testing, automation, and more. In my previous experience at Stress Free Solutions, I have gained experience working with large datasets and developing efficient data pipelines for the use of client-side web interaction. Another significant component of the role at Stress Free Solutions involved web design using the my knowledge of the “full-stack” to create a React application that uses MySQL, Python(Django), Javascript, and more. This field provides endless fascination to me and my goal is to make this my life's work.

  • I AM OBSESSED WITH: Data Structures, Data Visualization, and Machine Learning(Python), SQL, and of course 🎼🎵.

  • CURRENTLY WORKING ON:

SmartEstimator: A module of stressfreesolutionshomeimprovement.com that leverages image classification, invoice automation, NLP, and backend data management to provide a product that generates a predictive estimate based on customer input. This website was first created using ipage.com. As my fascination and passion for programming became more robust, I sought to build the website "from scratch". I re-created the boilerplate template of the original "drag and drop" site through the use of Wordpress and optimization with Drupal. My love of CSS and HTML manipulation was fostered at this point in the time with Stress Free Solutions. As time continued, I began to add more elements of object-oriented Javascript (React, Express) and back-end Python to make this website more dynamic.

Need Navigator: A tool implementing the use of Pyspark, SqlAlchemy, PostgreSQL, Textblob, Mlib, Seaborn, and Tensorflow to create a pipleline for the storage of data and educational performance analysis of students. Within those student entries there are fields that act as features('instrument', age, lesson time, what you worked on). There are also fields that are both categorical and numerical in nature that prompt the teacher to input both observational keywords(driven, redirection, etc) and a floating point number known as "Status" which are based on that week's lesson. "keywords" are observational, one-word monikers that describe the students performance in that week's lesson. "status" is a score that is the teacher's answer to the question, "How did it go with that student this week?". There is then is a subsequent script in this pipleline that extracts features/labels from the week's data where the features include all demographical information AND the subjective entries of Keywords and Status. The label/target column within this dataframe is WHAT you actually worked on in terms of lesson material. Here we then preprocess(vectorizes text, etc.) and interpret this data for the use of creating a student "Prescription" in terms of their needs on a particular subject at a particular point during their course of study. The "prescription" that is generated is a prediction concieved by a custom-fitted 1D convolutional neural network. This prediction then is fed into a different local Postgres database for the use of "looking up" past "prescriptions". This tool is intended to be used by teachers to track the needs of their students, but may have a variety of uses within the workplace. The total features which are "learned" by the model are both subjective and objective in nature and thus the "prescription" is more organic because it begs the NN to "walk in the shoes" of the teacher with regard to observing the student performance.

#turn it off first by commenting it out. #make it a variable if you need it more than once or if it's existence is unclear...else don't. #if it needs to be a variable, does it zig-zag through memory?

Releases

No releases published

Packages

No packages published