Introduction to TensorFlow
What you'll learn, and how you can apply it
- Understand what machine learning, neural networks, deep learning, and artificial intelligence are
- Discover what TensorFlow is and what applications it's good for
- Create deep learning models for classification and regression using TensorFlow
- Evaluate the benefits and disadvantages of using TensorFlow over other machine learning software
Who is this presentation for?
- You're a software engineer or programmer with a background in Python, and you wish to develop an understanding of machine learning.
- You have experience modeling or have a background in data science, and you would like to learn TensorFlow and deep learning.
- You're in a nontechnical role, and you would like to more effectively communicate with the engineers and data scientists in your company about TensorFlow and neural networks.
- Familiarity with Python, matrices, modeling, and statistics
- Introduction to TensorFlow
- Iterative algorithms
- Machine learning
- Basic neural networks
- Deep neural networks
- Variational autoencoders
- Convolutional neural networks
- Adversarial noise
- Recurrent neural networks
About your instructor
Robert Schroll is a data scientist in residence at the Data Incubator. Previously, he held postdocs in Amherst, Massachusetts, and Santiago, Chile, where he realized that his favorite parts of his job were teaching and analyzing data. He made the switch to data science and has been at the Data Incubator since. Robert holds a PhD in physics from the University of Chicago.
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