Cloud Platform 102 - Google Machine Learning with Cloud ML Class Description
This 1 day instructor led course builds upon Cloud Platform 100A and Cloud Platform CPB 101 (which are prerequisites). Through a combination of instructor-led presentations, demonstrations, and hands-on labs, Participants will deepen their familiarity with Machine Learning and Tensorflow concepts, whilst gaining hands-on skills in developing, evaluating, and productionizing machine learning models.
Course Benefits
- Participants will be definitively positioned on the cusp of workplace technology innovation, and predictive analytics.
- For those participants adequately qualified, this class represents an avenue to facilitate one’s own tangible improvements in workflow time, cost, and effort.
- Participants will be afforded the opportunity to become proficient at combining features and functions; building scalable and deployable models; and building one’s own Machine Learning Model
Who Should Attend
This class is intended for programmers and data scientists responsible for developing predictive analytics using machine learning. The typical audience member has experience analyzing and visualizing big data, implementing cloud-based big data solutions, and transforming/processing datasets.
Ideal individuals for this course have at least moderate knowledge of:
- Google Cloud Platform Big Data & Machine Learning Fundamentals to the level of Cloud Platform CPB100
- BigQuery and Dataflow to the level of Cloud Platform CPB 101
- Python and familiarity with the numpy package
- Undergraduate-level statistics to the level of Udacity ST101
Suggested Prerequisites
Related Classes
How to Enroll
EnrollmentPlease see our Enrollment Page (http://www.ledet.com/enroll) for our enrollment form.
Course Outline
By the end of this course, Students should know how to:
- Understand what kinds of problems machine learning can address
- Build a machine learning model using TensorFlow
- Build scalable, deployable ML models using Cloud ML
- Know the importance of preprocessing and combining features
- Incorporate advanced ML concepts into their models
- Employ ML APIs
- Productionize trained ML model
DisclaimerOur goal is to make sure your class meets your objectives, not ours. Therefore, all of our outlines are treated as guides to help steer the workshop. This outline does not guarantee that all the topics listed will be covered in the time allowed. The amount of material covered is based on the skill level of the student audience. We may change or alter course topics to best suit the classroom situation.
Locations
We have training centers in Atlanta, Houston, Chicago, Denver, San Diego and Washington DC. We also have the option of live instructor lead online offerings for our courses. Our network of rental facilities is also an option for most of our high demand classes. If coming to a rental facility, please double-check the location of your class with our office to make sure you get to the right location.
As an option for customers needing completely customizable training we offer private onsite training and Individual instructor consulting sessions. To inquire about custom training please fill out our private training request form.
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