Deep Learning with TensorFlow
9:00am - 5:00pm
What you'll learn, and how you can apply it
Participants will understand:
- What machine learning, neural networks, deep learning, and artificial intelligence are.
- What TensorFlow is and what applications it is good for.
Participants will be able to:
- Create deep learning models for classification and regression using TensorFlow.
- Evaluate the benefits and disadvantages of using TensorFlow over other machine learning software.
This training is for you because...
- You are 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 are in a non-technical role, and you would like to more effectively communicate with the engineers and data scientists in your company about TensorFlow and neural networks.
- Familiar with Python language
- Familiarity with matrices
- Familiarity with modeling
- Familiarity with statistics
No experience with TensorFlow is required.
- Introduction to Tensorflow
- Iterative Algorithms
- Machine Learning
- Basic Neural Networks
- Deep Neural Networks
- Variational Autoencoders
- Convolutional Neural Networks
- Adversarial Noise
- Recurrent Neural Network
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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