Hands-On Machine Learning on Google Cloud Platform: Implementing smart and efficient analytics using Cloud ML Engine

Hands-On Machine Learning on Google Cloud Platform: Implementing smart and efficient analytics using Cloud ML Engine

Hands-On Machine Learning on Google Cloud Platform: Implementing smart and efficient analytics using Cloud ML Engine

Hands-On Machine Learning on Google Cloud Platform: Implementing smart and efficient analytics using Cloud ML Engine

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Overview

Enhance your understanding of Computer Vision and image processing by developing real-world projects in OpenCV 3

Key Features

  • Get to grips with the basics of Computer Vision and image processing
  • This is a step-by-step guide to developing several real-world Computer Vision projects using OpenCV 3
  • This book takes a special focus on working with Tesseract OCR, a free, open-source library to recognize text in images

Book Description

Open CV is a cross-platform, free-for-use library that is primarily used for real-time Computer Vision and image processing. It is considered to be one of the best open source libraries that helps developers focus on constructing complete projects on image processing, motion detection, and image segmentation.

Whether you are completely new to the concept of Computer Vision or have a basic understanding of it, this book will be your guide to understanding the basic OpenCV concepts and algorithms through amazing real-world examples and projects.

Starting from the installation of OpenCV on your system and understanding the basics of image processing, we swiftly move on to creating optical flow video analysis or text recognition in complex scenes, and will take you through the commonly used Computer Vision techniques to build your own Open CV projects from scratch.

By the end of this book, you will be familiar with the basics of Open CV such as matrix operations, filters, and histograms, as well as more advanced concepts such as segmentation, machine learning, complex video analysis, and text recognition.

What You Will Learn

  • Install OpenCV 3 on your operating system
  • Create the required CMake scripts to compile the C++ application and manage its dependencies
  • Get to grips with the Computer Vision workflows and understand the basic image matrix format and filters
  • Understand the segmentation and feature extraction techniques
  • Remove backgrounds from a static scene to identify moving objects for video surveillance
  • Track different objects in a live video using various techniques
  • Use the new OpenCV functions for text detection and recognition with Tesseract

Who This Book Is For

If you are a software developer with a basic understanding of Computer Vision and image processing and want to develop interesting Computer Vision applications with Open CV, this is the book for you. Knowledge of C++ is required.


Product Details

ISBN-13: 9781788393485
Publisher: Packt Publishing
Publication date: 04/27/2018
Pages: 500
Product dimensions: 7.50(w) x 9.25(h) x 1.01(d)

About the Author

Prateek Joshi is a Computer Vision researcher and published author. He has over eight years of experience in this field with a primary focus on content-based analysis and deep learning. His work in this field has resulted in multiple patents, tech demos, and research papers at major IEEE conferences. He is the author of OpenCV with Python By Example, Packt Publishing. He has won many hackathons using a wide variety of technologies related to image recognition. His blog has been visited by users in more than 200 countries, and he has been featured as a guest author in prominent tech magazines. He enjoys blogging on topics, such as artificial intelligence, abstract mathematics, and cryptography. You can visit his blog at www.prateekvjoshi.com. He is an avid coder who is passionate about building game-changing products. He is particularly interested in intelligent algorithms that can automatically understand the content to produce scene descriptions in terms of constituent objects. He graduated from the University of Southern California and has worked for such companies as Nvidia, Microsoft Research, Qualcomm, and a couple of early stage start-ups in Silicon Valley. You can learn more about him on his personal website at www.prateekj.com.

Table of Contents

Table of Contents
  1. Setting up and Securing the Google Cloud Platform
  2. Interacting with Google Cloud Platform
  3. Google Cloud Storage
  4. Querying your data with BigQuery
  5. Transforming your data
  6. Essential Machine Learning
  7. Google Machine Learning APIs
  8. Creating Machine Learning Applications with Firebase
  9. Implementing a Feedforward network with TensorFlow and Keras
  10. Evaluating results with TensorBoard
  11. Optimizing your model with HyperTune
  12. Preventing Overfitting with regularization
  13. Beyond Feedforward networks
  14. Time series with LSTMs
  15. Reinforcement Learning with Tensorflow
  16. Generative neural networks
  17. Chatbots
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