Talk: Machine Learning with TensorFlow

Given as the August talk to Danbury AI.

TensorFlow™ is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google’s Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well.


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About the Author: Andrew Ribeiro

I am a computer scientist working in the field of Artificial Intelligence as the co-founder of Knowledge-Exploration Systems -- a Danbury based AI and systems development contractor. I studied traditional computer science at WCSU and extended my knowledge to include AI by taking online courses, reading the classic books, and reading research papers in the field while applying the ideas to commercial R&D applications. Due to the intensive intellectual demands of mastering such a diverse field, I also co-founded Danbury AI in 2016 to foster a local community of AI experts and enthusiasts that help each other grow and learn.

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