Hands-on Machine Learning with Python: Clustering, Dimension Reduction, and Time Series Analysis
This course will give you an overview of machine learning with Python. You will see and use the same tools that industry use. We will be using Jupyter and pandas to prepare data to analyze. We will look at common machine learning actions: clustering and dimension reduction. We will also use the prophet library to do time series forecasting.
What you'll learn-and how you can apply it
By the end of this live online course, you’ll understand:
- Basic machine learning tasks
- How to use Python and Jupyter to perform machine learning
And you’ll be able to:
- Use pandas to load and preprocess data
- Run dimension reduction, clustering, and time series analysis
This training course is for you because...
- You are a programmer and would like to see how to use Python for machine learning tasks of clustering, dimension reduction, and time series analysis.
- You are a data scientist with experience in SAS or R and would like an introduction to the Python ecosystem
- A url with a Jupyter notebook will be distributed to students prior to the class
- Familiarity with the Python programming language is useful, though if you have programming experience, you should be able to get through the course
- System Test:
To test whether you will be able to run the jupyter notebooks in your upcoming training, please:
Navigate here: https://attendee-testing.oreilly-jupyterhub.com (This is the link to the test site)
- Sign in with your Safari credentials
- Click "start my server"
Click on "notebook .ipynb"
Run each of the code cells: click the cell then either press Shift+Return or click the triangle in the top menu
There may be a few second delay, but you should eventually see the graphs. If you do not, this probably means that your firewall is blocking JupyterHub's websockets. Please turn off your company VPN or speak with your system administrator to allow.
Please come prepared with a clear schedule so you can participate in the hands-on portions. Rather than just listening to the instructor drone on, you will get the chance to try your hand at machine learning.
Materials or Downloads Needed in Advance:
Install Anaconda and Jupyter to try out on your own time
About your instructor
Matt runs MetaSnake, a Python and Data Science training and consulting company. He has over 15 years of experience using Python across a breadth of domains: Data Science, BI, Storage, Testing and Automation, Open Source Stack Management, and Search.
The timeframes are only estimates and may vary according to how the class is progressing
Introduction to Jupyter - 20 min
Common Data Cleaning Operations - 30 min
Break - 5 min
- Dimension Reduction - 40 min
Break - 5 min
- Clustering - 40 min
Break - 5 min
- Time series forecasting - 40 min