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Hands-On Machine Learning on Google Cloud Platform: Implementing smart and efficient analytics using Cloud ML Engine - Softcover
Synopsis
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.
"synopsis" may belong to another edition of this title.
About the Author
Alexis Perrier is a data science consultant with a background in signal processing and stochastic algorithms.
A former Parisian, Alexis is now actively involved in the D.C. data science community as an instructor, blogger, and presenter. Alexis is also an avid jazz and classical music fan, a book lover and proud owner of a real chalk blackboard on which he regularly tries to share his fascination with mathematical equations with his 3 children.
He holds a Master in Mathematics from Université Pierre et Marie Curie Paris VI, a Ph.D. in Signal Processing from Telecom ParisTech and currently resides in Washington D.C.
Follow him on twitter @alexip
Giuseppe Ciaburro holds a PhD in environmental technical physics and two master's degrees. His research was focused on machine learning applications in the study of the urban sound environments. He works at Built Environment Control Laboratory - Università degli Studi della Campania Luigi Vanvitelli (Italy). He has over 15 years of work experience in programming (Python, R, and MATLAB), first in the field of combustion and then in acoustics and noise control. He has several publications to his credit.
V Kishore Ayyadevara has over 9 years of experience of using analytics to solve business problems and setting up analytical work streams through his work at American Express, Amazon, and more recently a retail analytics consulting start-up. He is an MBA graduate from IIM Calcutta and also an electronics and communications engineer.
He worked in the fields of credit risk analytics, supply chain analytics, and consulting for multiple FMCG companies to identify ways to improve their profitability.
His interests lie in translating a business problem into a data-related problem by demystifying complexity in data science and identifying ways to further embed analytics in business.
"About this title" may belong to another edition of this title.
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Digital. Condition: 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. Seller Inventory # LU-9781788393485
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