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Application Development with TensorFlow & Keras

PYTH-150 (2 Days)

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TensorFlow & Keras Training Overview

Accelebrate's Application Development with TensorFlow & Keras training teaches attendees how to develop real-world machine learning applications powered by TensorFlow and Keras, popular technologies for building production-grade deep learning models. Students also learn how to use an HTTP API to retrieve model predictions.

Location and Pricing

Most Accelebrate courses are delivered as private, customized, on-site training at our clients' locations worldwide for groups of 3 or more attendees and are custom tailored to their specific needs. Please visit our client list to see organizations for whom we have delivered private in-house training. These courses can also be delivered as live, private online classes for groups that are geographically dispersed or wish to save on the instructor's or students' travel expenses. To receive a customized proposal and price quote for private training at your site or online, please contact us.

TensorFlow & Keras Training Objectives

All students will:

  • Understand the necessary technical requirements for developing a TensorFlow-powered application
  • Gain knowledge on different deep learning architectures and start to develop an intuition on what to chose for your problem
  • Experiment with different deep learning algorithms
  • Train and evaluate the performance of deep learning models
  • Combine your model with Flask to create an HTTP API that returns model predictions

TensorFlow & Keras Training Outline

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Introduction
  • Overview neural networks and deep learning
  • Organizing a project directory
  • Setting-up programming environment
Model Architecture
  • Load and prepare Bitcoin dataset
  • Overview of a TensorFlow computation graph (i.e. a "model")
  • Overview of the Keras interface
  • Deploying TensorBoard
Model Training and Evaluation
  • cl Training a model
  • Testing a model
  • Determining when to stop
  • Model deployment
Productization
  • Overview of an (extremely) simple Flask application
  • Creating an HTTP endpoint
  • Retrieving JSON results
Conclusion
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Lecture percentage

50%

Lecture/Demo

Lab percentage

50%

Lab

Course Number:

PYTH-150

Duration:

2 Days

Prerequisites:

All students should have programming experience, familiarity with Python 3, and basic knowledge of web-applications (i.e., how the HTTP protocol works). Knowledge of the following topics are useful, but not required:

  • Machine learning concepts such as the bias and variance tradeoff, and accuracy estimation methods
  • Familiarity with other machine learning algorithms such as Support Vector Machines, Adaptive Boosting (a.k.a. "AdaBoost"), Naïve Bayes, and Logistic Regression
  • Knowledge of statistics, probability, linear algebra, and calculus
  • Experience with data-provisioning systems, including file systems (local and remote) and databases (SQL and NoSQL)

Training Materials:

All TensorFlow students receive comprehensive courseware covering all topics in the class.

Software Requirements:

  • Windows, MacOS, or Linux
  • Anaconda or comparable Python distribution with TensorFlow and Keras installed
  • PyCharm, Spyder, or comparable Python IDE
  • Related lab files that Accelebrate provides
  • Internet access for all attendees and the instructor

Contact Us:

Accelebrate’s training classes are available for private groups of 3 or more people at your site or online anywhere worldwide.

Don't settle for a "one size fits all" public class! Have Accelebrate deliver exactly the training you want, privately at your site or online, for less than the cost of a public class.

For pricing and to learn more, please contact us.

Contact Us

Toll-free in US/Canada:
877 849 1850
International:
+1 678 648 3113

Toll-free in US/Canada:
866 566 1228
International:
+1 404 420 2491

925B Peachtree Street, NE
PMB 378
Atlanta, GA 30309-3918
USA

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