Hands-on Deep Learning For Images With Tensorfl... < Top 100 Validated >

: Understand natural language models to process both text and images simultaneously. Target Audience

: Learn to prepare datasets and transform raw image data into tensors for machine learning. Project Implementations : Develop models specifically for MNIST digits recognition. Build effective image classifiers using Docker and Keras . Hands-On Deep Learning for Images with TensorFl...

Create a to deploy your models.

is a practical guide written by Will Ballard and published by Packt Publishing in July 2018. This 96-page book focuses on implementing real-world computer vision projects using TensorFlow and Keras . Key Learning Objectives : Understand natural language models to process both

The book is designed for application developers, data scientists, and machine learning practitioners who want to integrate deep learning into software. To get the most out of the content, readers should have: A solid foundation in programming. A basic understanding of general deep learning concepts. Table of Contents Overview Hands-On Deep Learning for Images with TensorFlow - Packt Build effective image classifiers using Docker and Keras