Mar 15–18, 2020

Machine Learning from Scratch in TensorFlow

Robert Schroll (The Pragmatic Institute)
Sunday, March 15—Monday, March 16
Location: 212 AB

Participants should plan to attend both days of training course. Note: to attend training courses, you must be registered for a Platinum or Training pass; does not include access to tutorials on Monday.

The TensorFlow library provides for the use of computational graphs, with automatic parallelization across resources. This architecture is ideal for implementing neural networks. This training will introduce TensorFlow's capabilities in Python. It will move from building machine learning algorithms piece by piece to using the Keras API provided by TensorFlow with several hands-on applications.

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.

Who is this presentation for?

Data scientists or analysts




Familiar with Python language Familiarity with matrices Familiarity with modeling Familiarity with statistics No experience with TensorFlow is required.

Hardware and/or installation requirements:

A laptop computer

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

Photo of Robert Schroll

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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