Machine Learning With Core Ml 2 And Swift

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Machine Learning with Core ML 2 and Swift

Author : Karoly Nyisztor
Publisher : Independently Published
Page : 154 pages
File Size : 49,5 Mb
Release : 2018-10-21
Category : Electronic
ISBN : 1983292060

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Machine Learning with Core ML 2 and Swift by Karoly Nyisztor Pdf

Take a deep dive into machine learning with Core ML, and learn how to integrate common machine learning tasks into your apps. "Machine Learning with Core ML 2 and Swift" is a straightforward guide to the hottest topic in the tech industry. In this book, author Károly Nyisztor helps to familiarize you with common machine learning tasks. He introduces each concept using simple terms, avoiding confusing jargon. He focuses on the practical application, using hands-on Swift code examples you can use for reference and practice.Throughout the book, Károly walks you through several apps to familiarize yourself with Core ML capabilities, including synthetic vision and natural language processing.Topics include:- How to take advantage of Core ML- Setting up a Core ML project in Xcode- How to use pretrained models- Generating predictions- Using Vision- Image analysis- Natural language processing"Machine Learning with Core ML 2 and Swift" is the perfect book for you if you're interested in machine learning, or if you're looking to switch into an exciting new career track.About the AuthorKároly Nyisztor is a veteran mobile developer and instructor.He has built several successful iOS apps and games--most of which were featured by Apple--and is the founder at LEAKKA, a software development, and tech consulting company. He's worked with companies such as Apple, Siemens, SAP, and Zen Studios.

Mastering Machine Learning with Core ML and Python

Author : Vardhan Agrawal
Publisher : AppCoda
Page : 330 pages
File Size : 52,9 Mb
Release : 2020-08-13
Category : Computers
ISBN : 9789887535003

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Mastering Machine Learning with Core ML and Python by Vardhan Agrawal Pdf

Machine learning, now more than ever, plays a pivotal role in almost everything we do in our digital lives. Whether it’s interacting with a virtual assistant like Siri or typing out a message to a friend, machine learning is the technology facilitating those actions. It’s clear that machine learning is here to stay, and as such, it’s a vital skill to have in the upcoming decades. This book covers Core ML in-depth. You will learn how to create and deploy your own machine learning model. On top of that, you will learn about Turi Create, Create ML, Keras, Firebase, and Jupyter Notebooks, just to name a few. These are a few examples of professional tools which are staples for many machine learning experts. By going through this book, you’ll also become proficient with Python, the language that’s most frequently used for machine learning. Plus, you would have created a handful of ready-to-use apps such as barcode scanners, image classifiers, and language translators. Most importantly, you will master the ins-and-outs of Core ML.

Machine Learning with Core ML

Author : Joshua Newnham
Publisher : Packt Publishing Ltd
Page : 368 pages
File Size : 49,7 Mb
Release : 2018-06-28
Category : Computers
ISBN : 9781788835596

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Machine Learning with Core ML by Joshua Newnham Pdf

Leverage the power of Apple's Core ML to create smart iOS apps Key Features Explore the concepts of machine learning and Apple’s Core ML APIs Use Core ML to understand and transform images and videos Exploit the power of using CNN and RNN in iOS applications Book Description Core ML is a popular framework by Apple, with APIs designed to support various machine learning tasks. It allows you to train your machine learning models and then integrate them into your iOS apps. Machine Learning with Core ML is a fun and practical guide that not only demystifies Core ML but also sheds light on machine learning. In this book, you’ll walk through realistic and interesting examples of machine learning in the context of mobile platforms (specifically iOS). You’ll learn to implement Core ML for visual-based applications using the principles of transfer learning and neural networks. Having got to grips with the basics, you’ll discover a series of seven examples, each providing a new use-case that uncovers how machine learning can be applied along with the related concepts. By the end of the book, you will have the skills required to put machine learning to work in their own applications, using the Core ML APIs What you will learn Understand components of an ML project using algorithms, problems, and data Master Core ML by obtaining and importing machine learning model, and generate classes Prepare data for machine learning model and interpret results for optimized solutions Create and optimize custom layers for unsupported layers Apply CoreML to image and video data using CNN Learn the qualities of RNN to recognize sketches, and augment drawing Use Core ML transfer learning to execute style transfer on images Who this book is for Machine Learning with Core ML is for you if you are an intermediate iOS developer interested in applying machine learning to your mobile apps. This book is also for those who are machine learning developers or deep learning practitioners who want to bring the power of neural networks in their iOS apps. Some exposure to machine learning concepts would be beneficial but not essential, as this book acts as a launchpad into the world of machine learning for developers.

Machine Learning by Tutorials (Second Edition)

Author : raywenderlich Tutorial Team,Alexis Gallagher,Matthijs Hollemans,Audrey Tam,Chris LaPollo
Publisher : Unknown
Page : 128 pages
File Size : 52,5 Mb
Release : 2020-05-19
Category : Electronic
ISBN : 1942878931

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Machine Learning by Tutorials (Second Edition) by raywenderlich Tutorial Team,Alexis Gallagher,Matthijs Hollemans,Audrey Tam,Chris LaPollo Pdf

Learn Machine Learning!Machine learning is one of those topics that can be daunting at first blush. It's not clear where to start, what path someone should take and what APIs to learn in order to get started teaching machines how to learn.This is where Machine Learning by Tutorials comes in! In this book, we'll hold your hand through a number of tutorials, to get you started in the world of machine learning. We'll cover a wide range of popular topics in the field of machine learning, while developing apps that work on iOS devices.Who This Book Is ForThis books is for the intermediate iOS developer who already knows the basics of iOS and Swift development, but wants to understand how machine learning works.Topics covered in Machine Learning by TutorialsCoreML: Learn how to add a machine learning model to your iOS apps, and how to use iOS APIs to access it.Create ML: Learn how to create your own model using Apple's Create ML Tool.Turi Create and Keras: Learn how to tune parameters to improve your machine learning model using more advanced tools.Image Classification: Learn how to apply machine learning models to predict objects in an image.Convolutional Networks: Learn advanced machine learning techniques for predicting objects in an image with Convolutional Neural Networks (CNNs).Sequence Classification: Learn how you can use recurrent neural networks (RNNs) to classify motion from an iPhone's motion sensor.Text-to-text Transform: Learn how to use machine learning to convert bodies of text between two languages.By the end of this book, you'll have a firm understanding of what machine learning is, what it can and cannot do, and how you can use machine learning in your next app!

Machine Learning with Swift

Author : Oleksandr Sosnovshchenko,Oleksandr Baiev
Publisher : Packt Publishing Ltd
Page : 371 pages
File Size : 43,9 Mb
Release : 2018-02-28
Category : Computers
ISBN : 9781787123526

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Machine Learning with Swift by Oleksandr Sosnovshchenko,Oleksandr Baiev Pdf

Leverage the power of machine learning and Swift programming to build intelligent iOS applications with ease Key Features Implement effective machine learning solutions for your iOS applications Use Swift and Core ML to build and deploy popular machine learning models Develop neural networks for natural language processing and computer vision Book Description Machine learning as a field promises to bring increased intelligence to the software by helping us learn and analyse information efficiently and discover certain patterns that humans cannot. This book will be your guide as you embark on an exciting journey in machine learning using the popular Swift language. We’ll start with machine learning basics in the first part of the book to develop a lasting intuition about fundamental machine learning concepts. We explore various supervised and unsupervised statistical learning techniques and how to implement them in Swift, while the third section walks you through deep learning techniques with the help of typical real-world cases. In the last section, we will dive into some hard core topics such as model compression, GPU acceleration and provide some recommendations to avoid common mistakes during machine learning application development. By the end of the book, you'll be able to develop intelligent applications written in Swift that can learn for themselves. What you will learn Learn rapid model prototyping with Python and Swift Deploy pre-trained models to iOS using Core ML Find hidden patterns in the data using unsupervised learning Get a deeper understanding of the clustering techniques Learn modern compact architectures of neural networks for iOS devices Train neural networks for image processing and natural language processing Who this book is for iOS developers who wish to create smarter iOS applications using the power of machine learning will find this book to be useful. This book will also benefit data science professionals who are interested in performing machine learning on mobile devices. Familiarity with Swift programming is all you need to get started with this book.

Beginning Machine Learning in iOS

Author : Mohit Thakkar
Publisher : Apress
Page : 163 pages
File Size : 54,5 Mb
Release : 2019-02-20
Category : Computers
ISBN : 9781484242971

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Beginning Machine Learning in iOS by Mohit Thakkar Pdf

Implement machine learning models in your iOS applications. This short work begins by reviewing the primary principals of machine learning and then moves on to discussing more advanced topics, such as CoreML, the framework used to enable machine learning tasks in Apple products. Many applications on iPhone use machine learning: Siri to serve voice-based requests, the Photos app for facial recognition, and Facebook to suggest which people that might be in a photo. You'll review how these types of machine learning tasks are implemented and performed so that you can use them in your own apps. Beginning Machine Learning in iOS is your guide to putting machine learning to work in your iOS applications. What You'll LearnUnderstand the CoreML components Train custom models Implement GPU processing for better computation efficiency Enable machine learning in your application Who This Book Is For Novice developers and programmers who wish to implement machine learning in their iOS applications and those who want to learn the fundamentals about machine learning.

Practical Artificial Intelligence with Swift

Author : Mars Geldard,Jonathon Manning,Paris Buttfield-Addison,Tim Nugent
Publisher : O'Reilly Media
Page : 518 pages
File Size : 53,6 Mb
Release : 2019-09-03
Category : Computers
ISBN : 9781492044789

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Practical Artificial Intelligence with Swift by Mars Geldard,Jonathon Manning,Paris Buttfield-Addison,Tim Nugent Pdf

Create and implement AI-based features in your Swift apps for iOS, macOS, tvOS, and watchOS. With this practical book, programmers and developers of all kinds will find a one-stop shop for AI and machine learning with Swift. Taking a task-based approach, you’ll learn how to build features that use powerful AI features to identify images, make predictions, generate content, recommend things, and more. AI is increasingly essential for every developer—and you don’t need to be a data scientist or mathematician to take advantage of it in your apps. Explore Swift-based AI and ML techniques for building applications. Learn where and how AI-driven features make sense. Inspect tools such as Apple’s Python-powered Turi Create and Google’s Swift for TensorFlow to train and build models. I: Fundamentals and Tools—Learn AI basics, our task-based approach, and discover how to build or find a dataset. II: Task Based AI—Build vision, audio, text, motion, and augmentation-related features; learn how to convert preexisting models. III: Beyond—Discover the theory behind task-based practice, explore AI and ML methods, and learn how you can build it all from scratch... if you want to

Machine Learning Projects for Mobile Applications

Author : Karthikeyan NG
Publisher : Packt Publishing Ltd
Page : 246 pages
File Size : 52,6 Mb
Release : 2018-10-31
Category : Computers
ISBN : 9781788998468

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Machine Learning Projects for Mobile Applications by Karthikeyan NG Pdf

Bring magic to your mobile apps using TensorFlow Lite and Core ML Key FeaturesExplore machine learning using classification, analytics, and detection tasks.Work with image, text and video datasets to delve into real-world tasksBuild apps for Android and iOS using Caffe, Core ML and Tensorflow LiteBook Description Machine learning is a technique that focuses on developing computer programs that can be modified when exposed to new data. We can make use of it for our mobile applications and this book will show you how to do so. The book starts with the basics of machine learning concepts for mobile applications and how to get well equipped for further tasks. You will start by developing an app to classify age and gender using Core ML and Tensorflow Lite. You will explore neural style transfer and get familiar with how deep CNNs work. We will also take a closer look at Google’s ML Kit for the Firebase SDK for mobile applications. You will learn how to detect handwritten text on mobile. You will also learn how to create your own Snapchat filter by making use of facial attributes and OpenCV. You will learn how to train your own food classification model on your mobile; all of this will be done with the help of deep learning techniques. Lastly, you will build an image classifier on your mobile, compare its performance, and analyze the results on both mobile and cloud using TensorFlow Lite with an RCNN. By the end of this book, you will not only have mastered the concepts of machine learning but also learned how to resolve problems faced while building powerful apps on mobiles using TensorFlow Lite, Caffe2, and Core ML. What you will learnDemystify the machine learning landscape on mobileAge and gender detection using TensorFlow Lite and Core MLUse ML Kit for Firebase for in-text detection, face detection, and barcode scanningCreate a digit classifier using adversarial learningBuild a cross-platform application with face filters using OpenCVClassify food using deep CNNs and TensorFlow Lite on iOS Who this book is for Machine Learning Projects for Mobile Applications is for you if you are a data scientist, machine learning expert, deep learning, or AI enthusiast who fancies mastering machine learning and deep learning implementation with practical examples using TensorFlow Lite and CoreML. Basic knowledge of Python programming language would be an added advantage.

Machine Learning for iOS Developers

Author : Abhishek Mishra
Publisher : John Wiley & Sons
Page : 352 pages
File Size : 46,8 Mb
Release : 2020-03-04
Category : Computers
ISBN : 9781119602873

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Machine Learning for iOS Developers by Abhishek Mishra Pdf

Harness the power of Apple iOS machine learning (ML) capabilities and learn the concepts and techniques necessary to be a successful Apple iOS machine learning practitioner! Machine earning (ML) is the science of getting computers to act without being explicitly programmed. A branch of Artificial Intelligence (AI), machine learning techniques offer ways to identify trends, forecast behavior, and make recommendations. The Apple iOS Software Development Kit (SDK) allows developers to integrate ML services, such as speech recognition and language translation, into mobile devices, most of which can be used in multi-cloud settings. Focusing on Apple’s ML services, Machine Learning for iOS Developers is an up-to-date introduction to the field, instructing readers to implement machine learning in iOS applications. Assuming no prior experience with machine learning, this reader-friendly guide offers expert instruction and practical examples of ML integration in iOS. Organized into two sections, the book’s clearly-written chapters first cover fundamental ML concepts, the different types of ML systems, their practical uses, and the potential challenges of ML solutions. The second section teaches readers to use models—both pre-trained and user-built—with Apple’s CoreML framework. Source code examples are provided for readers to download and use in their own projects. This book helps readers: Understand the theoretical concepts and practical applications of machine learning used in predictive data analytics Build, deploy, and maintain ML systems for tasks such as model validation, optimization, scalability, and real-time streaming Develop skills in data acquisition and modeling, classification, and regression. Compare traditional vs. ML approaches, and machine learning on handsets vs. machine learning as a service (MLaaS) Implement decision tree based models, an instance-based machine learning system, and integrate Scikit-learn & Keras models with CoreML Machine Learning for iOS Developers is a must-have resource software engineers and mobile solutions architects wishing to learn ML concepts and implement machine learning on iOS Apps.

Mastering iOS 14 Programming

Author : Mario Eguiluz Alebicto,Chris Barker,Donny Wals
Publisher : Packt Publishing Ltd
Page : 559 pages
File Size : 50,8 Mb
Release : 2021-03-19
Category : Computers
ISBN : 9781838822606

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Mastering iOS 14 Programming by Mario Eguiluz Alebicto,Chris Barker,Donny Wals Pdf

Become a professional iOS developer with the most in-depth and advanced guide to Swift 5.3, Xcode 12.4, ARKit 4, Core ML, and iOS 14’s new features Key FeaturesExplore the world of iOS app development through practical examplesUnderstand core iOS programming concepts such as Core Data, networking, and the Combine frameworkExtend your iOS apps by adding augmented reality and machine learning capabilities, widgets, App Clips, Dark Mode, and animationsBook Description Mastering iOS 14 development isn’t a straightforward task, but this book can help you do just that. With the help of Swift 5.3, you’ll not only learn how to program for iOS 14 but also be able to write efficient, readable, and maintainable Swift code that reflects industry best practices. This updated fourth edition of the iOS 14 book will help you to build apps and get to grips with real-world app development flow. You’ll find detailed background information and practical examples that will help you get hands-on with using iOS 14's new features. The book also contains examples that highlight the language changes in Swift 5.3. As you advance through the chapters, you'll see how to apply Dark Mode to your app, understand lists and tables, and use animations effectively. You’ll then create your code using generics, protocols, and extensions and focus on using Core Data, before progressing to perform network calls and update your storage and UI with the help of sample projects. Toward the end, you'll make your apps smarter using machine learning, streamline the flow of your code with the Combine framework, and amaze users by using Vision framework and ARKit 4.0 features. By the end of this iOS development book, you’ll be able to build apps that harness advanced techniques and make the best use of iOS 14’s features. What you will learnBuild a professional iOS application using Xcode 12.4 and Swift 5.3Create impressive new widgets for your apps with iOS 14Extend the audience of your app by creating an App ClipImprove the flow of your code with the Combine frameworkEnhance your app by using Core LocationIntegrate Core Data to persist information in your appTrain and use machine learning models with Core MLCreate engaging augmented reality experiences with ARKit 4 and the Vision frameworkWho this book is for This book is for developers with some experience in iOS programming who want to enhance their application development skills by unlocking the full potential of the latest iOS version with Swift.

Intelligent Mobile Projects with TensorFlow

Author : Jeff Tang
Publisher : Packt Publishing Ltd
Page : 396 pages
File Size : 54,8 Mb
Release : 2018-05-22
Category : Computers
ISBN : 9781788628808

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Intelligent Mobile Projects with TensorFlow by Jeff Tang Pdf

Create Deep Learning and Reinforcement Learning apps for multiple platforms with TensorFlow Key Features Build TensorFlow-powered AI applications for mobile and embedded devices Learn modern AI topics such as computer vision, NLP, and deep reinforcement learning Get practical insights and exclusive working code not available in the TensorFlow documentation Book Description As a developer, you always need to keep an eye out and be ready for what will be trending soon, while also focusing on what's trending currently. So, what's better than learning about the integration of the best of both worlds, the present and the future? Artificial Intelligence (AI) is widely regarded as the next big thing after mobile, and Google's TensorFlow is the leading open source machine learning framework, the hottest branch of AI. This book covers more than 10 complete iOS, Android, and Raspberry Pi apps powered by TensorFlow and built from scratch, running all kinds of cool TensorFlow models offline on-device: from computer vision, speech and language processing to generative adversarial networks and AlphaZero-like deep reinforcement learning. You’ll learn how to use or retrain existing TensorFlow models, build your own models, and develop intelligent mobile apps running those TensorFlow models. You'll learn how to quickly build such apps with step-by-step tutorials and how to avoid many pitfalls in the process with lots of hard-earned troubleshooting tips. What you will learn Classify images with transfer learning Detect objects and their locations Transform pictures with amazing art styles Understand simple speech commands Describe images in natural language Recognize drawing with Convolutional Neural Network and Long Short-Term Memory Predict stock price with Recurrent Neural Network in TensorFlow and Keras Generate and enhance images with generative adversarial networks Build AlphaZero-like mobile game app in TensorFlow and Keras Use TensorFlow Lite and Core ML on mobile Develop TensorFlow apps on Raspberry Pi that can move, see, listen, speak, and learn Who this book is for If you're an iOS/Android developer interested in building and retraining others' TensorFlow models and running them in your mobile apps, or if you're a TensorFlow developer and want to run your new and amazing TensorFlow models on mobile devices, this book is for you. You'll also benefit from this book if you're interested in TensorFlow Lite, Core ML, or TensorFlow on Raspberry Pi.

Machine Learning for iOS Developers

Author : Abhishek Mishra
Publisher : John Wiley & Sons
Page : 461 pages
File Size : 46,8 Mb
Release : 2020-02-12
Category : Computers
ISBN : 9781119602903

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Machine Learning for iOS Developers by Abhishek Mishra Pdf

Harness the power of Apple iOS machine learning (ML) capabilities and learn the concepts and techniques necessary to be a successful Apple iOS machine learning practitioner! Machine earning (ML) is the science of getting computers to act without being explicitly programmed. A branch of Artificial Intelligence (AI), machine learning techniques offer ways to identify trends, forecast behavior, and make recommendations. The Apple iOS Software Development Kit (SDK) allows developers to integrate ML services, such as speech recognition and language translation, into mobile devices, most of which can be used in multi-cloud settings. Focusing on Apple’s ML services, Machine Learning for iOS Developers is an up-to-date introduction to the field, instructing readers to implement machine learning in iOS applications. Assuming no prior experience with machine learning, this reader-friendly guide offers expert instruction and practical examples of ML integration in iOS. Organized into two sections, the book’s clearly-written chapters first cover fundamental ML concepts, the different types of ML systems, their practical uses, and the potential challenges of ML solutions. The second section teaches readers to use models—both pre-trained and user-built—with Apple’s CoreML framework. Source code examples are provided for readers to download and use in their own projects. This book helps readers: Understand the theoretical concepts and practical applications of machine learning used in predictive data analytics Build, deploy, and maintain ML systems for tasks such as model validation, optimization, scalability, and real-time streaming Develop skills in data acquisition and modeling, classification, and regression. Compare traditional vs. ML approaches, and machine learning on handsets vs. machine learning as a service (MLaaS) Implement decision tree based models, an instance-based machine learning system, and integrate Scikit-learn & Keras models with CoreML Machine Learning for iOS Developers is a must-have resource software engineers and mobile solutions architects wishing to learn ML concepts and implement machine learning on iOS Apps.

AI and Machine Learning for On-Device Development

Author : Laurence Moroney
Publisher : "O'Reilly Media, Inc."
Page : 329 pages
File Size : 55,9 Mb
Release : 2021-08-12
Category : Computers
ISBN : 9781098101718

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AI and Machine Learning for On-Device Development by Laurence Moroney Pdf

Chapter 2. Introduction to Computer Vision -- Using Neurons for Vision -- Your First Classifier: Recognizing Clothing Items -- The Data: Fashion MNIST -- A Model Architecture to Parse Fashion MNIST -- Coding the Fashion MNIST Model -- Transfer Learning for Computer Vision -- Summary -- Chapter 3. Introduction to ML Kit -- Building a Face Detection App on Android -- Step 1: Create the App with Android Studio -- Step 2: Add and Configure ML Kit -- Step 3: Define the User Interface -- Step 4: Add the Images as Assets -- Step 5: Load the UI with a Default Picture.

Design Patterns in Swift 5: Learn how to Implement the Gang of Four Design Patterns Using Swift 5. Improve Your Coding Skills.

Author : Karoly Nyisztor
Publisher : Swift Clinic
Page : 300 pages
File Size : 50,7 Mb
Release : 2019-03-26
Category : Computers
ISBN : 1091686513

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Design Patterns in Swift 5: Learn how to Implement the Gang of Four Design Patterns Using Swift 5. Improve Your Coding Skills. by Karoly Nyisztor Pdf

Software developers need to solve various problems. Many times, these problems are the same or similar to the ones they've already encountered in other projects. Wouldn't it be great to apply the solution you've found instead of reinventing the wheel over and over again?That's precisely the reason why software design patterns exist. A design pattern is a standardized way to address a recurring problem. Relying on a proven strategy will not only save you time, but you can rest assured that it's indeed the right choice. Design patterns are the result of a long evolution process. It all started with a book published in 1994 - yes, it's that old! - called "Design Patterns - Elements of Reusable Object-Oriented Software." That's a quite tedious title, so we usually refer to it as "the book by the gang of four." The gang consists of four renowned software engineers: Erich Gamma, Ralph Johnson, Richard Helm, and John Vlissides. They identified the most significant common issues that occurred in multiple projects and developed best practices to solve them. The best part: these solutions are (programming) language-agnostic. You can use the design patterns with any object-oriented programming language. Many modern programming languages and frameworks have integrated the GoF patterns. You don't have to write additional code to support say the Iterator or the Observer.Swift is no exception. Actually, it provides many advanced language features and constructs --such as type extensions, lazy initialization, and predefined protocols -- that let us adopt and integrate the design patterns into our projects easily. This book covers all these topics and provides best practices you can apply in your upcoming projects.

Image Processing and Computer Vision in iOS

Author : Oge Marques
Publisher : Springer Nature
Page : 66 pages
File Size : 54,9 Mb
Release : 2020-11-23
Category : Computers
ISBN : 9783030540326

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Image Processing and Computer Vision in iOS by Oge Marques Pdf

This book presents the fundamentals of mobile visual computing in iOS development and provides directions for developers and researchers interested in developing iOS applications with image processing and computer vision capabilities. Presenting a technical overview of some of the tools, languages, libraries, frameworks, and APIs currently available for developing iOS applications Image Processing and Computer Vision in iOS reveals the rich capabilities in image processing and computer vision. Its main goal is to provide a road map to what is currently available, and a path to successfully tackle this rather complex but highly rewarding task.