Deep Learning Pipeline: Building a Deep Learning Model with Tensorflow - Paperback

by Hisham El-Amir (Author), Mahmoud Hamdy (Author)

Build your own pipeline based on modern TensorFlow approaches rather than outdated engineering concepts. This book shows you how to build a deep learning pipeline for real-life TensorFlow projects.

You'll learn what a pipeline is and how it works so you can build a full application easily and rapidly. Then troubleshoot and overcome basic Tensorflow obstacles to easily create functional apps and deploy well-trained models. Step-by-step and example-oriented instructions help you understand each step of the deep learning pipeline while you apply the most straightforward and effective tools to demonstrative problems and datasets.

• Develop a deep learning project using data
• Study and apply various models to your data
• Debug and troubleshoot the proper model suited for your data

Back Jacket

Build your own pipeline based on modern TensorFlow approaches rather than outdated engineering concepts. This book shows you how to build a deep learning pipeline for real-life TensorFlow projects.

You'll learn what a pipeline is and how it works so you can build a full application easily and rapidly. Then troubleshoot and overcome basic Tensorflow obstacles to easily create functional apps and deploy well-trained models. Step-by-step and example-oriented instructions help you understand each step of the deep learning pipeline while you apply the most straightforward and effective tools to demonstrative problems and datasets.

Author Biography

Hisham Elamir​ is a data scientist with expertise in machine learning, deep learning, and statistics. He currently lives and works in Cairo, Egypt. In his work projects, he faces challenges ranging from natural language processing (NLP), behavioral analysis, and machine learning to distributed processing. He is very passionate about his job and always tries to stay updated about the latest developments in data science technologies, attending meetups, conferences, and other events.

Mahmoud Hamdy is a machine learning engineer who works in Egypt and lives in Egypt, His primary area of study is the overlap between knowledge, logic, language, and learning. He works helping train machine learning, and deep learning models to distil large amounts of unstructured, semi-structured, and structured data into new knowledge about the world by using methods ranging from deep learning to statistical relational learning. He applies strong theoretical and practical skills in several areas of machine learning to finding novel and effective solutions for interesting and challenging problems in such interconnections