Beginning Application Development with TensorFlow and Keras

Free Download Udemy Beginning Application Development with TensorFlow and Keras. With the help of this course you can Learn to design, develop, train, and deploy TensorFlow and Keras models as real-world applications.

This course was created by Packt Publishing. It was rated 4.4 out of 5 by approx 12565 ratings. There are approx 28319 users enrolled with this course, so don’t wait to download yours now. This course also includes 4.5 hours on-demand video, 1 Downloadable Resource, Full lifetime access, Access on mobile and TV & Certificate of Completion.

What Will You Learn?

  • Learn ways to select the right model architecture

  • Make predictions with a trained model and work with TensorBoard

  • Evaluate metrics and techniques to deploy a model as a web application

  • Set up a deep learning programming environment

  • Explore components of a neural network and its essential operations

  • Deploy model as an interactive web application with Flask and HTTP API

  • Learn to use Keras, a TensorFlow abstraction library

  • Explore types of problems that are addressed by neural networks

With this course, you’ll learn how to train, evaluate, and deploy Tensorflow and Keras models as real-world web applications. After a hands-on introduction to neural networks and deep learning, you’ll use a sample model to explore details of deep learning and learn to select the right layers that can solve a given problem. By the end of the course, you’ll build a Bitcoin application that predicts the future price, based on historic and freely available information.

About the Author

Nimish Narang has a degree in biology and computer science. He has worked with application development and machine learning. His recent achievement was building the biggest ever mobile machine learning course which has many different machine learning and deep learning models in Python and translated into both Android and iOS applications to incorporate some elements of machine learning into mobile application.

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