soft-kelly/tutorials

Tutorial notebooks for hands-on data science, following along with the course topics.

Tutorials

This repository is a set of tutorials for Hands-On Data Science and Machine Learning in order for you to prepare necessary development environment for UC San Diego course COGS118A - Introduction to Machine Learning I. These tutorials presume some knowledge of the Python programming language.

Acknowledgment / Reference

This repo is a fork of original author who developed great tutorial set for UC San Diego course COGS108 - Data Science in Practice.

These tutorials are designed to be a minimal introduction to what you need to know to get working with data science - to start to be able getting and examing data, and building up to working on data-science related projects. They cover the hands-on, coding components of the material.

Conceptual and background material is covered in the Lectures. Practice with these ideas is done through the Assignments as well as materials for doing Projects.

These tutorials also try to interface with the vast world of existing tutorials, materials, and documentation. They are explicitly designed to give a quick introduction to a topic of interest, and then link out to more comprehensive resources. In that sense, they are designed to be more like a yellow pages, than an encyclopedia.

Requirements

The code and materials in this repository are created with Jupyter notebooks and require the anaconda distribution. Any other dependencies, for specific Tutorials, are specifically addressed in the notebooks.

Development

This repository is under active development, and is primarily developed and maintained by TomDonoghue, as well as by the COGS108 staff.

Contributions to this resource are welcome and encouraged! If you have suggestions for new links or materials, and/or fixes for any issues you spot, you are welcome and invited to open Issues, and/or submit a Pull Request.