Packt+ | Advance your knowledge in tech

0

All Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

Machine Learning with TensorFlow 1.x

You're reading from Machine Learning with TensorFlow 1.x Second generation machine learning with Google's brainchild - TensorFlow 1.x

Product type Paperback

Published in Nov 2017

Publisher Packt

ISBN-13 9781786462961

Length 304 pages

Edition 1st Edition

Languages

Python

Tools

TensorFlow

Concepts

Machine Learning

Authors (3):

Hua

Ahmed

Ul Azeem

View More author details

Table of Contents (19) Chapters

Title Page

Credits

About the Authors

About the Reviewer

www.PacktPub.com

Customer Feedback

Preface

1. Getting Started with TensorFlow FREE CHAPTER

2. Your First Classifier

3. The TensorFlow Toolbox

4. Cats and Dogs

5. Sequence to Sequence Models-Parlez-vous Français?

6. Finding Meaning

7. Making Money with Machine Learning

8. The Doctor Will See You Now

9. Cruise Control - Automation

10. Go Live and Go Big

11. Going Further - 21 Problems

12. Advanced Installation

TensorFlow-based Projects

In this section, we will introduce you to several problems that are implemented in TensorFlow and open-source on Github. We suggest that you take a look at these projects and learn how to improve your TensorFlow skills.

Problem 10 - Human Pose Estimation

Project Link: https://github.com/eldar/pose-tensorflow

This project is the open-source implementation of Deep Cut and ArtTrack in human body pose estimation. The goal of this project is to jointly solve the tasks of detection and pose estimation. We can use this method for various applications such as person detection in security or human action understanding. This project also provides great starting points for a lot of further research on human shape estimation with applications for virtual-try-on or garment recommendation.

Problem 11 - Object Detection - YOLO

Project link: https://github.com/thtrieu/darkflow

Object detection is an interesting problem in Computer Vision. There are lots of methods to solve this problem...

The rest of the chapter is locked

Register for a free Packt account to unlock a world of extra content!

A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.

Unlock this book and the full library FREE for 7 days

Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of

Start free trial

Renews at £13.99/month. Cancel anytime

Authors (3)

Hua

Hua

Quan Hua is a Computer Vision and Machine Learning Engineer at BodiData, a data platform for body measurements, where he focuses on developing computer vision and machine learning applications for a handheld technology capable of acquiring a body avatar while a person is fully clothed. He earned a bachelor of science degree from the University of Science, Vietnam, specializing in Computer Vision. He has been working in the field of computer vision and machine learning for about 3 years at start-ups. Quan has been writing for Packt since 2015 for a Computer Vision book, OpenCV 3 Blueprints.

See other products by Hua

Ahmed

Ahmed

Saif Ahmed is an accomplished quantitative analyst and data scientist with 15 years of industry experience. His career started in management consulting at Accenture and lead him to quantitative and senior management roles at Goldman Sachs and AIG Investments. Most recently, he co-founded and runs a start-up focused on applying Deep Learning to automating medical imaging. He obtained his bachelor's degree in computer science from Cornell University and is currently pursuing a graduate degree in data science at U.C. Berkeley.

See other products by Ahmed

Ul Azeem

Ul Azeem

Shams Ul Azeem is an undergraduate in electrical engineering from NUST Islamabad, Pakistan. He has a great interest in the computer science field, and he started his journey with Android development. Now, hes pursuing his career in Machine Learning, particularly in deep learning, by doing medical-related freelancing projects with different companies. He was also a member of the RISE lab, NUST, and he has a publication credit at the IEEE International Conference, ROBIO as a co-author of Designing of motions for humanoid goalkeeper robots.

See other products by Ul Azeem

Other recommended products

Related to this chapter

Neural Network Programming with Tensorflow

Neural Network Programming with Tensorflow

If you're aware of the buzz surrounding the terms such as machine learning, artificial intelligence or deep learning, you might know what neural networks are. TensorFlow is a popular framework which can be used to implement efficient neural networks and deep learning models. This book will show you how to leverage the power of TensorFlow to train efficient neural networks. You will start with understanding the fundamentals and basic math for neural networks and why TensorFlow is a popular choice of tool for programming neural networks. During the course of the book, you will be working on real-world datasets to get a hands-on understanding of neural network programming. By the end of this book, you will have a fair understanding of how you can leverage the power of TensorFlow to train neural networks of varying complexities, without any hassle. While you are learning about various neural network implementations you will learn the underlying mathematics and linear algebra and how it maps to the appropriate TensorFlow constructs.

Mastering TensorFlow 1.x

Mastering TensorFlow 1.x

We cover advanced deep learning concepts (such as transfer learning, generative adversarial models, and reinforcement learning), and implement them using TensorFlow and Keras. We cover how to build and deploy at scale with distributed models. You will learn to build TensorFlow models using R, Keras, TensorFlow Learn, TensorFlow Slim and Sonnet

Jan 2018 15h 48m

Deep Learning for Computer Vision

Deep Learning for Computer Vision

Deep learning has shown its power in several application areas of Artificial Intelligence, especially in Computer Vision, the science of manipulating and processing images. In this book, you will learn different techniques in deep learning to accomplish tasks related to object classification, object detection, image segmentation, captioning, image generation, and more. You will also explore their application using the popular Python libraries such as TensorFlow and Keras. With practical examples, you will learn to develop Computer Vision applications by leveraging the power of deep learning.

Jan 2018 10h 20m

Deep Learning with TensorFlow

Deep Learning with TensorFlow

Machine learning is concerned with algorithms for transforming data into actionable intelligence and predictive analytics. Deep learning is a branch of machine learning based on multiple levels of representations. This book introduces the core concepts of deep learning using the latest version of TensorFlow to get implementation and research details on cutting-edge architectures. You will learn deep learning with the hands-on model building, data collection and transformation and even more!

Apr 2017 10h 40m

What's New in TensorFlow 2.0

What's New in TensorFlow 2.0

This book will cover all the new features that have been introduced in TensorFlow 2.0 especially the major highlight, including eager execution and more. You will learn how to make the best use of these features to migrate your codes from TensorFlow 1.x to TensorFlow 2.0 in a seamless way.

Aug 2019 6h 44m

TensorFlow Machine Learning Cookbook

TensorFlow Machine Learning Cookbook

This book will help you overcome any problem you might come across while training and deploying machine learning models using the recently released Tensorflow. This book includes recipes on important machine learning concepts such as supervised and unsupervised learning, as well as neural networks and their real-world applications.

Aug 2018 14h 4m

Python Deep Learning Cookbook

Python Deep Learning Cookbook

Deep Learning is a rapidly evolving field of Machine Learning science which gives machines the ability to learn from information. This book contains detailed recipes to tackle with the common and not so common problems while dealing with deep learning algorithms and models in Python. You will benefit from this book by finding technical solutions to the issues presented, along with a detailed explanation of the solutions, and a discussion on corresponding pros and cons of implementing the proposed solution using Theano, Tensorflow, MXNet, and Keras. You'll come across recipes on data pre-processing, network models and topologies, supervised and unsupervised learning presented in a “solution to problem” fashion.

Oct 2017 11h 0m

TensorFlow 2.0 Computer Vision Cookbook

TensorFlow 2.0 Computer Vision Cookbook

This book covers recipes for solving various computer vision tasks using TensorFlow, taking you through all the tips and tricks you need to overcome any challenges that you may face while building various computer vision applications. You will discover machine learning techniques to solve problems in image processing, feature extraction, and more.

Feb 2021 18h 4m

Computer Vision Projects with OpenCV and Python 3

Computer Vision Projects with OpenCV and Python 3

This book demonstrates techniques to leverage the power of Python, OpenCV, and TensorFlow to solve problems in Computer Vision. This book also shows you how to build an application that can estimate human poses within images. You will also classify images and identify humans in videos, and then develop your own handwritten digit classifier.

TensorFlow 1.x Deep Learning Cookbook

TensorFlow 1.x Deep Learning Cookbook

Deep Neural Networks (DNNs) have achieved a lot of success in the field of computer vision, speech recognition, and natural language processing. In this book, you will learn how to efficiently use TensorFlow, Google's open source framework for deep learning, and implement different deep learning networks with easy to follow independent recipes.

Dec 2017 17h 52m

Hands-On Deep Learning with TensorFlow

Hands-On Deep Learning with TensorFlow

With deep learning going mainstream, making sense of data and getting accurate results using deep networks is possible. Dan Van Boxel is your guide to exploring the possibilities with deep learning; he will enable you to understand data like never before. With the efficiency and simplicity of TensorFlow, you will be able to process your data and gain insights that will change how you look at data.

Jul 2017 5h 48m

Hands-On Computer Vision with TensorFlow 2

Hands-On Computer Vision with TensorFlow 2

Computer vision is achieving a new frontier of capabilities in fields like health, automobile or robotics. This book explores TensorFlow 2, Google's open-source AI framework, and teaches how to leverage deep neural networks for visual tasks. It will help you acquire the insight and skills to be a part of the exciting advances in computer vision.

May 2019 12h 24m

Personalised recommendations for you

Based on your interests and search pattern

Mathematics of Machine Learning

Mathematics of Machine Learning

Deepen your theoretical knowledge and enhance your ability to solve complex machine learning problems with structured guidance. Gain the confidence to engage with advanced ML literature and tailor algorithms to meet your project requirements.

May 2025 24h 20m

Generative AI with Python and PyTorch

Generative AI with Python and PyTorch

Learn how to create images and text using VAEs, GANs, LSTMs, and transformers. Implement applications in natural language processing and computer vision through practical tutorials.

Mar 2025 15h 0m

Practical Generative AI with ChatGPT

Practical Generative AI with ChatGPT

This book helps you unlock ChatGPT's potential to make your working life better. From prompt engineering to creating custom GPTs, you'll enhance your productivity, creativity, and efficiency with practical insights and advanced techniques.

Apr 2025 12h 52m

Generative AI with LangChain

Generative AI with LangChain

Gain a solid foundation in LangChain, agentic AI, and LangGraph, and learn to build production-ready systems with multi-agent architectures, advanced RAG pipelines, Tree of Thought reasoning, agent handoffs, and fine-grained error handling.

May 2025 15h 52m

Architecting Power BI Solutions in Microsoft Fabric

Architecting Power BI Solutions in Microsoft Fabric

Power BI provides several options to solve common data problems, and designing the correct solution for each scenario can be a daunting task. This book makes it easier by guiding you through designing optimal solutions using Power BI.

Apr 2025 14h 16m

Microsoft Identity and Access Administrator SC-300 Exam Guide

Microsoft Identity and Access Administrator SC-300 Exam Guide

This comprehensive guide covers key topics such as Microsoft Entra ID implementation, authentication and access management, external user management, and hybrid identity solutions, providing practical insights and techniques for SC-300 exam success.

Mar 2025 19h 48m

LLM Design Patterns

LLM Design Patterns

This book helps you gain practical skills to develop and deploy LLMs. You'll learn data prep, training, pruning, quantization, and evaluation, as well as explore RAG, advanced prompting, and optimization to build robust, scalable language models.

May 2025 17h 48m

Tableau Cookbook for Experienced Professionals

Tableau Cookbook for Experienced Professionals

Advance your Tableau knowledge beyond the basics, streamline dashboard performance, tackle advanced geospatial challenges, and unlock API potential while fortifying your corporate data infrastructure with proven best practices.

Apr 2025 12h 24m

Time Series Analysis with Spark

Time Series Analysis with Spark

This book offers a complete guide to time series analysis with Apache Spark and Databricks, covering essential concepts and advanced techniques including Generative AI to equip readers with skills for real-world challenges across industries.

Mar 2025 9h 56m

Hands-On Artificial Intelligence for IoT

Hands-On Artificial Intelligence for IoT

Transform IoT systems with the power of artificial intelligence using this hands-on guide. Dive into practical techniques and expert insights to innovate and optimize your IoT devices, making them smarter and more efficient.

May 2025 15h 44m