All course materials for the Zero to Mastery Machine Learning and Data Science course.

Docker Mastery Udemy course to build, compose, deploy, and manage containers from local development to high-availability in the cloud

Awesome-LLM: a curated list of Large Language Model

Code repository for O'Reilly book

Self-study on Larry Wasserman's "All of Statistics"

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

A collection of algorithms and data structures

Datasets used in Plotly examples and documentation

Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

Open source platform for the machine learning lifecycle

Text and supporting code for Think Stats, 2nd Edition

Jupyter notebook and datasets from the pandas Q&A video series

All the data for the Public Policy Analytics book by Ken Steif can be downloaded from this repo

Self study on Cryer and Chan's "Time series analysis with applications in R"

Data Visualizations for New York City

Public repository for course materials for the Data Science at Scale Specialization at Coursera

My solution to the book A Collection of Data Science Take-Home Challenges

Data Science Resources (Mostly Free)