Deep Learning Pipeline

Deep Learning Pipeline

  • Author: Hisham El-Amir, Mahmoud Hamdy
  • ISBN: 1484253485
  • Year: 2019
  • Pages: 551
  • Language: English
  • File size: 12 MB
  • File format: PDF, ePub
  • Category: Programming


Book Description:

Build your own pipeline based on contemporary TensorFlow approaches instead of outdated engineering theories. This book shows you how you can build a deep learning pipeline for real-life TensorFlow projects.

You’ll learn exactly what a pipeline is and how it functions so it’s possible to build a full application easily and quickly. Then troubleshoot and overcome fundamental Tensorflow obstacles to readily create functional programs and install well-trained models. Step-by-step and example-oriented instructions help you understand each step of this profound learning pipeline while you employ the simplest and effective tools to demonstrative troubles and datasets.

You will also develop a deep learning project by preparing data, choosing the model that matches that data, and then resizing your model to get the best fit to information all using Tensorflow methods. Enhance your skills by accessing some of the most effective recent trends in data science. If you have ever considered building your own picture or text-tagging solution or entering a Kaggle contest, Deep Learning Pipeline is for you!

What You’ll Learn

  • Create a profound learning project using information
  • Study and employ many models to your data
  • Debug and troubleshoot the proper model suited for your information

Who This Book Is For

Programmers, analysts, and information scientists seeking to add to enhance their presentation skills by accessing a number of the most effective recent trends in data science. Prior experience in Python or other TensorFlow-associated languages and mathematics would be helpful.

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