This lesson series asks students to use a machine learning specialization to explore multiple case studies between various predictive models and analyze an intelligent application that makes predictions from data.
Personalized PG&E usage data is readily available for customers, but what can this data tell us?
In this lesson series, students learn about the role of reliability engineering in product development and then engage in a math modeling experience using data related to reliability experiments from my fellowship at Facebook Reality Labs.
Semiconductors are the backbones of electronic devices that are commonly used by people today. A lot of people know and use these common electronic devices such as smartphones, video game consoles, and automobiles.
The purpose of STEM Talks! is to give high school students the opportunity to talk to scientists about their career and/or how their job is related to math and science.
From the moment we wake up, our brains use data to help us understand the world around us and act accordingly. We don’t only gather data for the sake of it. We don’t even do it with the purpose of analyzing it, but for it’s interpretation and implications that this has.
In order to make informed decisions, students must know how to properly analyze and interpret data. This is one of the main learning goals in my physics classes.
The purpose of this ETP is to provide physics teachers a bite-sized approach to begin implementing design thinking into their scope and sequence.
A fundamental aspect of how Deep Learning systems work is that they make predictions about how a function should fit some test dataset, evaluate the errors from that function to the test dataset, and modify that function to reduce the errors.