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Beginning Application Development with TensorFlow and Keras Training

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Description

This course covers the development of a real-world application powered by TensorFlow and Keras. TensorFlow is popular software created by Google (and open source contributors) to facilitate the development of machine learning applications, particularly those that use deep learning. Keras is an interface that facilitates the development of deep learning models. 

The course starts with a hands-on introduction to TensorFlow and Keras. Then we move to the architecture of an example model, selecting the right layers to solve an example problem (predicting Bitcoin prices). Then we move on to the training and evaluation of the model. We will finish by deploying the model as a real-world product: a web-application (with an HTTP API) that uses Flask to make our model predictions available to the world.

This is a 2-day course packaged with the right balance of theory and hands-on activities that will help you easily learn TensorFlow and Keras from scratch. 

This course will provide you with a blueprint of how to build an application that generates predictions using a deep learning model. From there you can continue to improve the example model—either by adding more data, computing more features, or changing its architecture—continuously increasing its prediction accuracy, or create a completely new model, changing the core components of the application as you see fit.

Bring This Course To You

For groups of 5 or more, let Intertech bring this course to your location. Customized versions tailored towards your objectives are also available.

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Audience

This course is designed for developers, analysts, and data scientists interested in developing applications using TensorFlow and Keras. 

Course Outline

Lesson 1: Introduction to Neural Networks and Deep Learning

  • What are Neural Networks?
  • Configuring a Deep Learning Environment

Lesson 2: Model Architecture

  • Choosing the Right Model Architecture
  • Using Keras as a TensorFlow Interface

Lesson 3: Model Evaluation and Evaluation

  • Model Evaluation
  • Hyperparameter Optimization

Lesson 4: Productization

  • Handling New Data
  • Deploying a Model as a Web Application

Free Resources from Intertech

Free On-Demand Video Bundle: IoT, Agile/Scrum, and Leadership

Free Whitepaper: Design and Code Review Checklist

Free eBook: Mastering The Daily Agile Stand-Up

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