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  • šŸ‘‹ Hi, Iā€™m William Kubin
  • šŸ‘€ Iā€™m interested in DevOps Engineering, Data Science/Analytics, Machine Learning, Cloud Computing
  • šŸŒ± Iā€™m currently learning Computational Science (Ph.D.)
  • šŸ’žļø Iā€™m looking to collaborate on data science/data analytics and computational science projects
  • šŸ“« How to reach me: [email protected]

William Kubin's Projects

3tier_app_k8s_aws icon 3tier_app_k8s_aws

In this project, I orchestrate a 3-tier php application on a Kubernetes cluster. The application consists of a frontend (php app), a backend (database management tool), and a database (mysql). I automated the launch of two AWS EC2 Instances as Master and Worker Nodes using Terraform and Ansible respectively.

aws_ci-cd_pipeline icon aws_ci-cd_pipeline

In this project, I implemented a continuous integration/continuous deployment (CI/CD) pipeline from GitHub to AWS EC2 Instance.

aws_cloudformationproject icon aws_cloudformationproject

In this project, I implement AWS Infrastructure with an Infrastructure as Code (IaC) service CloudFormation

complete_ci_cd_project_03 icon complete_ci_cd_project_03

This project is a continuation of Complete_CI_CD_Project_02. I add a deployment of the dockerized web app on Amazon ECS

completeci_cd_pipeline icon completeci_cd_pipeline

In this project, I create infrastructure in AWS using Terraform (IaC) and use them to build a CI/CD pipeline for a java web app. I deploy the app on a tomcat server.

creditcardapproval-artificialneuralnetwork icon creditcardapproval-artificialneuralnetwork

In this project, we analyze and predit the approval ratings of credit cards with respect to features including gender, age, debt, married, bank customer, industry, ethnicity, years employed, prior default, employed, credit score, driver's license, citizen, zipcode, income and approved (target feature) using a deep learning model (Artificial Neural Network (ANN)). We use precision, recall, f1-score to measure performance of our ANN model.

creditcardapproval-kmeansclustering icon creditcardapproval-kmeansclustering

In this project, we analyze data on customers behavior with respect to their credit card usage. We employ KMeans clustering algorithm (an unsupervised machine learning model) to discover natural groupings in feature space in the data.

creditcardapproval-logisticregression icon creditcardapproval-logisticregression

In this project, I analyze the approval ratings of credit cards with respect to features including gender, age, debt, married, bank customer, industry, ethnicity, years employed, prior default, employed, credit score, driver's license, citizen, zipcode, income and approved (target feature).

creditcardapproval-variousclassificationmodelpredictions icon creditcardapproval-variousclassificationmodelpredictions

In this project, we apply various classification models (6) to the credit card data to examine their corresponding performance. The models include simple linear algorithms {Logistic Regression (LRG), Linear Discriminant Analysis (LDA)} and non-linear algorithms {K-Nearest Neighbors (KNN), Classification and Regression Trees (CART), Gaussian Naive Bayes (GNB), Support Vector Machines (SVM)}

dfa icon dfa

Detrended Fluctuation Analysis

examples icon examples

Helm chart repository for example charts

fathon icon fathon

python package for DFA (Detrended Fluctuation Analysis) and related algorithms

gdp-time-series-project icon gdp-time-series-project

This project provides a realistic forecast based on latest available data to reflect current state of the economy of Switzerland. The aim is to develop a model that can accurately predict the economic growth rate of Switzerland using the dataset that is available from dataseries.org website

geolocation_helm icon geolocation_helm

Deployment of docker image of geolocation application to Kubernetes cluster using Helm

heart-failure-prediction-project icon heart-failure-prediction-project

This project illustrates the prediction of Heart Failure in people. The data used for the analysis has 299 observations with 13 variables namely age, anemia, creatinine phosphokinase, diabetes, ejection fraction, high blood pressure, platelets, serum creatinine, serum sodium, sex, smoking, time and the TARGET variable death event

k8s_devops_project icon k8s_devops_project

In this project, we I use Kubernetes to implement a real-world project where Mongo Express UI is connected with MongoDB and the Mongo Express makes requests to the DataBase.

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