While understanding machine learning has never been easier, it helps to know how to get started on some of the latest tools and features that are available. In this hands-on workshop with Galvanize, you’ll learn the very basics of machine learning via the language of Python.
Our community of staff, students, and professional instructors will guide you through the elementary aspects of SciKit Learn, a popular machine learning library for the Python language. We will learn a bit more about matrices, develop a linear model on a real data set, and play around in the sandbox if we have time.
You’ll leave this session equipped to write your own scripts and feel more prepared to take the next steps on your path to understanding machine learning.
Note: Maximum Attendance 35 due to space constraints and preserving the quality of education.
What to Bring
Your laptop and charger
Please have the following installed:
What You’ll Learn
• Fundamental concepts of machine learning: modeling and generalizability
• A bit of review of linear algebra, especially matrices
• How to create a linear regression model on some real data
• How to use Scikit Learn within a Python Jupyter notebook
6:30 pm – Networking & Announcements
6:40 pm – Machine Learning: the fundamental concepts
6:50 pm – Setting up your computer in Anaconda for Jupyter Notebooks
7:00 pm – Getting started with Scikit Learn
7:30 pm – Exploring the database and building a linear model
8:15 pm – Wind down, sandboxing & Q&A
8:30 pm – HARD STOP
This is a beginner workshop, but some background on Python in data science would certainly help. Participants who are familiar with concepts of data analysis and statistics will be better equipped to apply their skills after the conclusion of the workshop.
We recommend the following options:
About our Sponsor
Galvanize is the premiere dynamic learning community for technology. With campuses located in booming technology sectors throughout the country, Galvanize provides a community for each the following:
To learn more about Galvanize, visit galvanize.com.