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Name: Ryan Ellis

Type: User

Bio: I am a nerd with a deep interest in machine learning. I am passionate about exploring emerging technologies and experimenting with innovative solutions.

Hi, I'm Ryan 👋

I'm a Software Developer and Data Science Specialist with a passion for machine learning and solving complex problems. With a Bachelor's degree in Computer Science from UMBC, I specialize in leveraging Python, C, and C++ to build innovative solutions.

💡 Technical Skills

Languages:

Python, C, C++, C#, HTML, CSS, Javascript, MATLAB, R, SQL

Libraries:

Python Libraries:
- TensorFlow, PyTorch, Scikit-learn, Pandas, OpenCV, OpenAI, Beautifulsoup
Frameworks:
- .NET, React

Tools:

Git, Docker, Jupyter

🚀 Projects

Personal Projects

RAG Chatbot Example - This is an example of a python script using Retrieval-augmented generation. The goal of the bot was to use a blog as the source for the RAG.
- Languages Used: Python
- Libraries Used: OpenAI, Pandas, Langchain, ChromaDB
- Concepts Demonstrated: RAG, Chatbot
IBM Capstone Project - Demonstrates examining space X rocket data and present findings. This demonstrates EDA with visualizations and predictive analysis with machine learning.
- Languages Used: Python, SQL
- Libraries Used: Space X API, Pandas
- Concepts Demonstrated: EDA, Predictive Analysis

College Projects/Repositories:

Baltimore Crime Data Project - College project that utilized NodeJS to make a heat map of crime in the Baltimore area.
- Languages Used: NodeJs, TypeScript, JavaScript
Computer-Science-II - This repository contains class projects for the Computer Science II class which taught Object Oriented Programming.
- Languages Used: C++
- Concepts Demonstrated: Object Oriented Programming
Introduction to Machine Learning - This repository contains class work for the Introduction to Machine Learning course at UMBC. This course taught the basics of machine learning.
- Languages Used: Python, HTML
- Concepts Demonstrated: Classification

📫 Let's Connect

LinkedIn: Ryan Ellis
Email: [email protected]

Ryan Ellis's Projects

aitensorflowspecialization

My notes for coursera course AI TensorFlow in Practice Specialization.

bcr_app

Hackathon Fall 2019 buissness card reading app

cmsc471-spring2020

Files, slides, notes, and Jupyter Notebooks of CMSC471-AI class in Spring 2020. All rights reserved. Fereydoon Vafaei UMBC

codeblockz

comfyui

The most powerful and modular stable diffusion GUI, api and backend with a graph/nodes interface.

computer-science-ii

coursera-machine-learning-engineering-for-prod-mlops-specialization-personal-notes

Programming assignments and quizzes from all courses within the Machine Learning Engineering for Production (MLOps) specialization offered by deeplearning.ai

crewai_bloger_demo

data-science-self-projects

This is a collection of self data science projects that demonstrate various machine learning techniques.

datasets

🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools

deepfacelab

DeepFaceLab is the leading software for creating deepfakes.

dlaicourse

Notebooks for learning deep learning

ellis_ryan_applieddatasciencecapstone

This is a collection of notebooks that I used while taking the Coursera Course Applied Data Science Capstone.

handson-ml

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

jobbot

A automatic job search and application filler!

langchainshortcourseellisnotes

This is a personal repository for the short course LangChain for LLM Application Development. This is meant to be a personal repository showing my experimentation with Langchain while learning it.

materials_for_experiments

Bonus materials, exercises, and example projects for our Python tutorials

portfolio

Portfolio Website from Ryan Ellis

sql-practice

This repository exist for the purpose of personal practice and learning of SQL

umbc-cmsc-478-fall-2019

Lecture slides, Jupyter Notebooks, code and scripts for CMSC 478 - Introduction to Machine Learning

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