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mkasulecoder/README.md

Hello
Fancy seeing you here!

I am Mark Kasule

## πŸš€ Software Engineer & Data Scientist Extraordinaire

I'm a Software and Machine Learning Engineer based in Washington D.C., specializing in user-friendly frontend UIs and robust backend systems while integrating Machine Learning models into applications. With over 7 years of experience, I have made significant impacts across various agencies, consulted for startups, and collaborated with talented teams to develop digital products in sectors like Material Science, E-commerce, Real Estate, Healthcare, Finance, and Insurance. Let's collaborate to drive innovation and create impactful solutions for your business challenges.

πŸ’» What I Do

  • Build web apps that are so responsive, they finish your sentences before you do (Django and Spring Boot are my trusty sidekicks)
  • Tame wild datasets and turn them into well-behaved insights (Pandas is my animal whisperer)
  • Create machine learning models that predict the future (or at least try to - my crystal ball is still in beta)
  • Visualize data so beautifully, it makes bar charts blush (Power BI is my artistic medium of choice)

🧠 My Superpowers

  • Python (I can Python faster than a snake can slither)
  • Java (I spring into action with Spring Boot)
  • Javascript - React.Js & NextJs
  • Data Analysis (I find needles in haystacks, then analyze the hay)
  • Machine Learning (Teaching machines to learn, so I don't have to)
  • PyTorch (Lighting up neural networks like it's the 4th of July)
  • Django (Making web frameworks as cool as the Django theme song)

AWS | NoSQL MongoDB | SQL - Postgres | PowerBI | Scikit-Learn | Pandas | Numpy

🎭 When I'm Not Coding

  • Explaining recursion to my dog (he's still chasing his tail, but we're making progress)
  • Debugging production issues (because who needs sleep, right?)
  • Trying to convince my coffee maker to integrate with my smart home system

🌟 Why You Should Work With Me

  1. I turn coffee into code, and code into solutions
  2. I can speak to databases in their native tongue (SQL, NoSQL, or interpretive dance)
  3. My code is so clean, it squeaks when you compile it
  4. I've never met a bug I couldn't squash (except for that one time... we don't talk about that)

So, if you're looking for someone who can wrangle data, build robust web applications, and crack a few jokes along the way, you've come to the right profile. Let's build something amazing together – and maybe teach a few machines to laugh at our jokes while we're at it!

P.S. If you have a coding problem, I'm your guy. If you have a bug infestation, please call an exterminator. I only debug digital critters!

πŸ˜ƒ Did I mention that..

"I code. I caffeinate. I repeat. When I'm not debugging, I'm probably googling. My superpower? Turning coffee into code. In my free time, I like to tinker with machines, break things, and then fix them again (sometimes). Oh, and I'm pretty sure I can write a program to solve world hunger, I just haven't had enough coffee yet."

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🧩 Did you Know?

β€œDebugging is like being a detective in a crime movie where you are also the murderer.”

My life in loops πŸ”

GitHub Streak

🚧 Technologies

Next.js Django Java JavaScript React Nodejs Python C++ HTML5 CSS3 Bootstrap TypeScript MongoDB GraphQL Apollo GraphQL PostgreSQL MySQL Heroku Docker Amazon AWS Google Cloud Git GitHub GitLab BitBucket Linux

Pinned Loading

  1. movie-api-database movie-api-database Public

    This is a movie api developed for backend services for a movie application with reviews from users

    Java 1 1

  2. myexpensehabits myexpensehabits Public

    This web App tracks your expense habits and displays your net salary!

    HTML

  3. kc_housing_price_predictor kc_housing_price_predictor Public

    πŸ€– Housing Price ML model Predictor

    Jupyter Notebook

  4. heartdisease_decision_tree_model_ML heartdisease_decision_tree_model_ML Public

    A heart disease machine learning model thats built with the decision tree classifier

    Jupyter Notebook

  5. stroke_prediciton_clustering_model_ML stroke_prediciton_clustering_model_ML Public

    An unsupervised model to group patients with heart disease in clusters using the KMeans algorithm to predict stokes