Skip to content Skip to site navigation Skip to service navigation

Machine Learning Basics

Class Sessions

Date Location Cost
  • Thu May 30, 9:00 am to 4:00 pm
Birch Hall 105 (Birch Lab A) $405
  • Fri Jul 12, 9:00 am to 4:00 pm
Redwood Hall G6 (POST) $405

Class Code

ITS-1903

Class Description

This class helps in awareness about Machine Learning patterns and use cases in real world, and help you understand the different ML techniques. Learn about popular ML offerings, and utilize Jupyter Notebooks to perform hands-on labs.

After this course, you will be able to:  

  • Describe the role of Machine Learning and where it fits into Information Technology strategies
  • Explain the technical and business drivers that result from using Machine Learning
  • Describe Supervised and Unsupervised learning techniques and usages
  • Understand techniques like Classification, Clustering and Regression
  • Discuss how to identify which kinds of technique to be applied for specific use case
  • Understand the popular Machine offerings like Amazon Machine Learning, TensorFlow, Azure Machine Learning, Spark mlib, Python and R etc.
  • Install and Setup Anaconda.
  • Perform hands-on activity using Jupyter Notebooks.

 

Topic Outline:

Course Introduction

  • History and background of Machine Learning
  • Compare Traditional Programming Vs Machine Leaning 
  • Supervised and Unsupervised Learning Overview
  • Machine Learning patterns
    - Classification
    - Clustering
    - Regression
  • Gartner Hype Cycle for Emerging Technologies
  • Machine Learning offerings in Industry
  • Hands-on exercise 1: Install and Setup Anaconda.
  • Python Libraries
    - NumPy
    - Pandas
    - Scikit Learn
  • Hands-on exercise 2: Data Analysis using Pandas
  • Algorithms
    - Linear Regression
    - Decision Tree
    - Random Forest
    - K-Means Clustering
  • Hands-on exercise 3: Perform Linear regression using Scikit-learn
  • Hands-on exercise 4: Perform Decision tree on Titanic Data set using Scikit-learn
  • References and Next steps
     


University IT Technology Training classes are only available to Stanford University staff, faculty, or students. A valid SUNet ID is needed in order to enroll in a class.