Machine Learning from Scratch in TensorFlow
Sunday, March 15—Monday, March 16
What you'll learn, and how you can apply it
Who is this presentation for?
Hardware and/or installation requirements:
The TensorFlow library provides for the use of data flow graphs for numerical computations, with automatic parallelization across several CPUs or GPUs. This architecture makes it ideal for implementing neural networks and other machine learning algorithms. This training will introduce TensorFlow’s capabilities through its Python interface. It will move from building machine learning algorithms piece by piece to using the Keras API provided by TensorFlow. Students will use this knowledge to build machine-learning models on real-world data. Students will also be provisioned a cloud instance with Tensorflow as a part of this course
About your instructor
San Jose Instructor: Robert Schroll obtained his Ph.D. in Physics from the University of Chicago before completing postdocs in Amherst, Massachusetts, and Santiago, Chile. There, he realized that the favorite parts of his job were teaching and analyzing data. He made the switch to data science and has been teaching at the Data Incubator for the past year.
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