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Hands-On Machine Learning on Google Cloud Platform: Implementing smart and efficient analytics using Cloud ML Engine - Softcover
Inhaltsangabe
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.
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Über die Autorin bzw. den Autor
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.
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Digital. Zustand: New. Unleash Google's Cloud Platform to build, train and optimize machine learning modelsAbout This Book. Get well versed in GCP pre-existing services to build your own smart models. A comprehensive guide covering aspects from data processing, analyzing to building and training ML models. A practical approach to produce your trained ML models and port them to your mobile for easy accessWho This Book Is ForThis book is for data scientists, machine learning developers and AI developers who want to learn Google Cloud Platform services to build machine learning applications. Since the interaction with the Google ML platform is mostly done via the command line, the reader is supposed to have some familiarity with the bash shell and Python scripting. Some understanding of machine learning and data science concepts will be handyWhat You Will Learn. Use Google Cloud Platform to build data-based applications for dashboards, web, and mobile. Create, train and optimize deep learning models for various data science problems on big data. Learn how to leverage BigQuery to explore big datasets. Use Google's pre-trained TensorFlow models for NLP, image, video and much more. Create models and architectures for Time series, Reinforcement Learning, and generative models. Create, evaluate, and optimize TensorFlow and Keras models for a wide range of applicationsIn DetailGoogle Cloud Machine Learning Engine combines the services of Google Cloud Platform with the power and flexibility of TensorFlow. With this book, you will not only learn to build and train different complexities of machine learning models at scale but also host them in the cloud to make predictions.This book is focused on making the most of the Google Machine Learning Platform for large datasets and complex problems. You will learn from scratch how to create powerful machine learning based applications for a wide variety of problems by leveraging different data services from the Google Cloud Platform. Applications include NLP, Speech to text, Reinforcement learning, Time series, recommender systems, image classification, video content inference and many other. We will implement a wide variety of deep learning use cases and also make extensive use of data related services comprising the Google Cloud Platform ecosystem such as Firebase, Storage APIs, Datalab and so forth. This will enable you to integrate Machine Learning and data processing features into your web and mobile applications.By the end of this book, you will know the main difficulties that you may encounter and get appropriate strategies to overcome these difficulties and build efficient systems.Style and approachAn easy-to-follow step by step guide which will help you get to the grips with real-world applications of Google Cloud Machine Learning. Bestandsnummer des Verkäufers LU-9781788393485
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Bestandsnummer des Verkäufers 9781788393485
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Digital. Zustand: New. Unleash Google's Cloud Platform to build, train and optimize machine learning modelsAbout This Book. Get well versed in GCP pre-existing services to build your own smart models. A comprehensive guide covering aspects from data processing, analyzing to building and training ML models. A practical approach to produce your trained ML models and port them to your mobile for easy accessWho This Book Is ForThis book is for data scientists, machine learning developers and AI developers who want to learn Google Cloud Platform services to build machine learning applications. Since the interaction with the Google ML platform is mostly done via the command line, the reader is supposed to have some familiarity with the bash shell and Python scripting. Some understanding of machine learning and data science concepts will be handyWhat You Will Learn. Use Google Cloud Platform to build data-based applications for dashboards, web, and mobile. Create, train and optimize deep learning models for various data science problems on big data. Learn how to leverage BigQuery to explore big datasets. Use Google's pre-trained TensorFlow models for NLP, image, video and much more. Create models and architectures for Time series, Reinforcement Learning, and generative models. Create, evaluate, and optimize TensorFlow and Keras models for a wide range of applicationsIn DetailGoogle Cloud Machine Learning Engine combines the services of Google Cloud Platform with the power and flexibility of TensorFlow. With this book, you will not only learn to build and train different complexities of machine learning models at scale but also host them in the cloud to make predictions.This book is focused on making the most of the Google Machine Learning Platform for large datasets and complex problems. You will learn from scratch how to create powerful machine learning based applications for a wide variety of problems by leveraging different data services from the Google Cloud Platform. Applications include NLP, Speech to text, Reinforcement learning, Time series, recommender systems, image classification, video content inference and many other. We will implement a wide variety of deep learning use cases and also make extensive use of data related services comprising the Google Cloud Platform ecosystem such as Firebase, Storage APIs, Datalab and so forth. This will enable you to integrate Machine Learning and data processing features into your web and mobile applications.By the end of this book, you will know the main difficulties that you may encounter and get appropriate strategies to overcome these difficulties and build efficient systems.Style and approachAn easy-to-follow step by step guide which will help you get to the grips with real-world applications of Google Cloud Machine Learning. Bestandsnummer des Verkäufers LU-9781788393485
Anzahl: Mehr als 20 verfügbar