Just a laptop with a web browser.
Incorporating machine learning capabilities into software or apps is quickly becoming a necessity rather than a “nice to have” feature, and open source machine learning framework TensorFlow is becoming an industry standard.
Rich Ott leads you through two days of intensive learning that include a review of linear algebra essential to machine learning, an introduction to TensorFlow, and a dive into neural networks. You’ll master simple machine learning models such as classification and regression models, construct and launch graphs in TensorFlow by using TensorBoard to visualize workflow, and build and test models in TensorFlow using real-world data. You’ll leave with both a theoretical and practical understanding of the algorithms behind machine learning and be ready to incorporate them into your next project.
The class will be taught using TensorFlow’s Python interface.
Day 1
Exercises
Day 2
Exercises
Richard Ott obtained his PhD in particle physics from the Massachusetts Institute of Technology, followed by postdoctoral research at the University of California, Davis. He then decided to work in industry, taking a role as a data scientist and software engineer at Verizon for two years. When the opportunity to combine his interest in data with his love of teaching arose at The Data Incubator, he joined and has been teaching there ever since.
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Comments
We’ll be working on cloud servers, so just a laptop with a web browser. We’ve found Chrome and Firefox tend to work best
What do we need to bring to training and have set up before we start?