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

License: Apache License 2.0

Jupyter Notebook 99.67% Makefile 0.01% Shell 0.01% Python 0.31% Dockerfile 0.01%

handson-ml's Introduction

Hi, I'm Ryan ๐Ÿ‘‹

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.

๐Ÿ’ก 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

๐Ÿš€ 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

๐Ÿ“ซ Let's Connect

handson-ml's People

Contributors

abhinav-upadhyay avatar ageron avatar aidancooper avatar barrald avatar brokenairplane avatar cezcz avatar chrisqlasty avatar daniel-s-ingram avatar dcthetall avatar dependabot[bot] avatar dgwozdz avatar drorata avatar francotheengineer avatar jasrys avatar jdaviestx avatar jirkalhotka avatar kxrr avatar lujunweng avatar lvnilesh avatar mmoffitt avatar nbgraham avatar pkourdis avatar psnilesh avatar qinhanmin2014 avatar rickiepark avatar saied89 avatar stefan-it avatar stevenbunkley avatar vladimir-tikhonov avatar ziembla avatar

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