mazrk7/machine_learning_resources
Machine learning resources (Jupyter notebooks mostly). Originally code to complement the "EECE 5644: Introduction to Machine Learning and Pattern Recognition" course taught at Northeastern University.
This collection of Jupyter notebooks provides practical examples and code implementations for fundamental machine learning and pattern recognition concepts. It helps students understand complex algorithms by showing both the mathematical theory and how to code them in Python. Students taking an introductory machine learning course would find this useful for hands-on learning.
No commits in the last 6 months.
Use this if you are a student or educator looking for clear, runnable examples that demonstrate core machine learning principles.
Not ideal if you are a seasoned machine learning practitioner seeking advanced, production-ready code or a comprehensive library for your own projects.
Stars
22
Forks
4
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Oct 23, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/mazrk7/machine_learning_resources"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
GeostatsGuy/MachineLearningCourse
My graduate level machine learning course, including student machine learning projects.
neural-data-science/NESC_3505_textbook
Textbook for NESC 3505, Neural Data Science, at Dalhousie University
snrazavi/Machine_Learning_2018
Codes and Project for Machine Learning Course, Fall 2018, University of Tabriz
tuanavu/coursera-university-of-washington
University of Washington
gerdm/prml
Repository of notes, code and notebooks in Python for the book Pattern Recognition and Machine...