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Machine Learning Is For Everyone

Most Technology Training classes will be delivered online until further notice.

Before each sesson, Tech Training will provide a Zoom link for live online classes, along with any required class materials.

 

 

This introductory lecture helps in awareness about Machine Learning patterns and use cases in real world. We'll review statistics and data analytics to drive all participants to be more data-minded, providing an understanding of the Data Science process.
 

After this course, you will be able to:

  • 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
  • Machine Learning patterns
    - Classification
    - Clustering
    - Regression
  • Gartner Hype Cycle for Emerging Technologies
  • Machine Learning offerings in Industry
  • Exercise 1 - Install and Setup Anaconda.
  • Python Libraries
    - NumPy
    - Pandas
    - Scikit Learn
  • Exercise 2: Data Analysis using Pandas
  • Algorithms
    - Linear Regression
    - Decision Tree
  • Exercise 3: Perform Linear regression using Scikit-learn
  • References and Next steps
Antony Ross

Antony originally attained a degree in psychology with an emphasis in sport psychology. He began working with athletes and eventually chose to pursue a graduate degree in exercise physiology. He conducted research in muscle physiology while teaching at USC and, subsequently, UCLA.

Custom training workshops are available for this program

Technology training sessions structured around individual or group learning objectives. Learn more about custom training

University IT Technology Training sessions are available to a wide range of participants, including Stanford University staff, faculty, students, and employees of Stanford Hospitals & Clinics, such as Stanford Health Care, Stanford Health Care Tri-Valley, Stanford Medicine Partners, and Stanford Medicine Children's Health.

Additionally, some of these programs are open to interested individuals not affiliated with Stanford, allowing for broader community engagement and learning opportunities.