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Machine Learning with TensorFlow

New – Learn second generation machine learning with Google's brainchild - TensorFlow 1.x in this self-paced course.

GK# 7733

Course Overview

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TensorFlow is an open source software library for numerical computation using data flow graphs. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. This course will approach common commercial machine learning problems using Google’s TensorFlow library. It will cover unique features of the library such as Data Flow Graphs, training, visualization of performance with TensorBoard – all within an example-rich context using problems from multiple industries. The focus will be towards introducing new concepts through problems which are coded and solved over the course of each section.

Schedule

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What You'll Learn

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  • Explore how to use different machine learning models to ask different questions of your data
  • Learn how to build deep neural networks using TensorFlow 1.x
  • Cover key tasks such as clustering, sentiment analysis, and regression analysis using TensorFlow 1.x
  • Find out how to write clean and elegant Python code that will optimize the strength of your algorithms
  • Discover how to embed your machine learning model in a web application for increased accessibility
  • Learn how to use multiple GPUs for faster training using AWS

Outline

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On-Demand Outline

Getting Started with TensorFlow

Your First Classifier

Your First Classifier

Cats and Dogs - Working with Images

Parlez-vous Francais? – Translate Text

Finding Meaning - Sentiment Analysis

Making Money from Machine Learning

The Doctor Will See You Now

Cruise Control: Automation

Go Live and Go Big

Migrating from Existing Platforms

Going Further: 21 Problems

Appendix A: Advanced Installation

Who Should Attend

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This course is for data scientists and researchers who are looking to either migrate from an existing machine learning library or jump into a machine learning platform headfirst. The course is also for software developers who wish to learn deep learning by example. Particular focus is placed on solving commercial deep learning problems from several industries using TensorFlow’s unique features. No commercial domain knowledge is required, but familiarity with Python and matrix math is expected.

Course Delivery

This course is available in the following formats:

On-Demand

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