Presented By
O’Reilly + Cloudera
Make Data Work
March 25-28, 2019
San Francisco, CA
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Machine learning from scratch in TensorFlow

Robert Schroll (The Data Incubator)
Monday, March 25 & Tuesday, March 26, 9:00am - 5:00pm
Data Science, Machine Learning & AI
 Location: 2014
Secondary topics:  Deep Learning
Average rating: ****.
(4.50, 2 ratings)

Participants should plan to attend both days of this 2-day training course. To attend training courses, you must register for a Platinum or Training pass; does not include access to tutorials on Tuesday.

The TensorFlow library provides for the use of computational graphs, with automatic parallelization across resources. This architecture is ideal for implementing neural networks. Robert Schroll offers an overview of TensorFlow's capabilities in Python, demonstrating how to build machine learning algorithms piece by piece and how to use TensorFlow's Keras API with several hands-on applications.

What you'll learn, and how you can apply it

  • Understand machine learning, neural networks, deep learning, and artificial intelligence basic concepts
  • Learn 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

This training is for you because...

  • You're a software engineer or programmer who wants to develop a basic understanding of machine learning.
  • You have experience modeling or have a background in data science, and you want to learn TensorFlow.

Prerequisites:

  • A working knowledge of Python
  • Familiarity with matrices, modeling, and statistics
  • No experience with TensorFlow required

Hardware and/or installation requirements:

  • A WiFi-enabled machine (You'll be provisioned a cloud instance with TensorFlow.)

The TensorFlow library provides for the use of computational graphs, with automatic parallelization across resources. This architecture is ideal for implementing neural networks. Robert Schroll offers an overview of TensorFlow’s capabilities in Python, demonstrating how to build machine learning algorithms piece by piece and how to use TensorFlow’s Keras API with several hands-on applications.

Outline

Day 1

  • Introduction to TensorFlow
  • Iterative algorithms
  • Machine learning
  • Basic neural networks

Day 2

  • Deep neural networks
  • Variational autoencoders
  • Convolutional neural networks
  • Adversarial noise
  • DeepDream
  • Recurrent neural networks

About your instructor

Photo of Robert Schroll

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.

Conference registration

Get the Platinum pass or the Training pass to add this course to your package.

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Comments

Eric Leschinski | SOFTWARE DEVELOPER
03/20/2019 5:41am PDT

Is there a detailed info with information about what version of Tensorflow, Keras, Cloud profisioned OS, and which version of python so we can know what to expect and be prepared?