Machine Learning For Ios Developers

Machine Learning For Ios Developers Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Machine Learning For Ios Developers book. This book definitely worth reading, it is an incredibly well-written.

Machine Learning with Core ML

Author : Joshua Newnham
Publisher : Packt Publishing Ltd
Page : 368 pages
File Size : 54,8 Mb
Release : 2018-06-28
Category : Computers
ISBN : 9781788835596

Get Book

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 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

Get Book

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.

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 : 48,9 Mb
Release : 2020-05-19
Category : Electronic
ISBN : 1942878931

Get Book

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!

AI and Machine Learning for On-Device Development

Author : Laurence Moroney
Publisher : "O'Reilly Media, Inc."
Page : 329 pages
File Size : 45,5 Mb
Release : 2021-08-12
Category : Computers
ISBN : 9781098101718

Get Book

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.

Machine Learning

Author : Jason Bell
Publisher : John Wiley & Sons
Page : 432 pages
File Size : 45,6 Mb
Release : 2020-03-10
Category : Mathematics
ISBN : 9781119642145

Get Book

Machine Learning by Jason Bell Pdf

Dig deep into the data with a hands-on guide to machine learning with updated examples and more! Machine Learning: Hands-On for Developers and Technical Professionals provides hands-on instruction and fully-coded working examples for the most common machine learning techniques used by developers and technical professionals. The book contains a breakdown of each ML variant, explaining how it works and how it is used within certain industries, allowing readers to incorporate the presented techniques into their own work as they follow along. A core tenant of machine learning is a strong focus on data preparation, and a full exploration of the various types of learning algorithms illustrates how the proper tools can help any developer extract information and insights from existing data. The book includes a full complement of Instructor's Materials to facilitate use in the classroom, making this resource useful for students and as a professional reference. At its core, machine learning is a mathematical, algorithm-based technology that forms the basis of historical data mining and modern big data science. Scientific analysis of big data requires a working knowledge of machine learning, which forms predictions based on known properties learned from training data. Machine Learning is an accessible, comprehensive guide for the non-mathematician, providing clear guidance that allows readers to: Learn the languages of machine learning including Hadoop, Mahout, and Weka Understand decision trees, Bayesian networks, and artificial neural networks Implement Association Rule, Real Time, and Batch learning Develop a strategic plan for safe, effective, and efficient machine learning By learning to construct a system that can learn from data, readers can increase their utility across industries. Machine learning sits at the core of deep dive data analysis and visualization, which is increasingly in demand as companies discover the goldmine hiding in their existing data. For the tech professional involved in data science, Machine Learning: Hands-On for Developers and Technical Professionals provides the skills and techniques required to dig deeper.

Machine Learning with Swift

Author : Oleksandr Sosnovshchenko,Oleksandr Baiev
Publisher : Packt Publishing Ltd
Page : 371 pages
File Size : 52,8 Mb
Release : 2018-02-28
Category : Computers
ISBN : 9781787123526

Get Book

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.

AI and Machine Learning On-Device Development

Author : Laurence Moroney
Publisher : Unknown
Page : 124 pages
File Size : 44,8 Mb
Release : 2021
Category : Electronic
ISBN : 1098101731

Get Book

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

AI is nothing without somewhere to run it. Now that mobile devices have become the primary computing device for most people, it's essential that mobile developers add AI to their toolbox. This insightful book is your guide to creating models and running them on popular mobile platforms such as iOS and Android. Laurence Moroney, lead AI advocate at Google, offers an introduction to machine learning techniques and tools, then walks you through writing Android and iOS apps powered by common ML models like computer vision and text recognition, using tools such as ML Kit, TensorFlow Lite, and Core ML. If you're a mobile developer, this book will help you take advantage of the ML revolution today. Explore the options for implementing ML and AI on mobile devices--and when to use each Create ML models for iOS and Android Write ML Kit and TensorFlow Lite apps for iOS and Android and Core ML/Create ML apps for iOS Understand how to choose the best techniques and tools for your use case: on-device inference versus cloud-based inference, high-level APIs versus low-level APIs, and more Learn privacy and ethics best practices for ML on devices.

Beginning Machine Learning in iOS

Author : Mohit Thakkar
Publisher : Apress
Page : 163 pages
File Size : 51,5 Mb
Release : 2019-02-20
Category : Computers
ISBN : 9781484242971

Get Book

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 : 46,8 Mb
Release : 2019-09-03
Category : Computers
ISBN : 9781492044789

Get Book

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

MatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition: Emerging Research and Opportunities

Author : Wu, Jiann-Ming,Tien, Chao-Yuan
Publisher : IGI Global
Page : 181 pages
File Size : 43,9 Mb
Release : 2020-04-17
Category : Computers
ISBN : 9781799815563

Get Book

MatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition: Emerging Research and Opportunities by Wu, Jiann-Ming,Tien, Chao-Yuan Pdf

Deep learning has become a trending area of research due to its adaptive characteristics and high levels of applicability. In recent years, researchers have begun applying deep learning strategies to image analysis and pattern recognition for solving technical issues within image classification. As these technologies continue to advance, professionals have begun translating this intelligent programming language into mobile applications for devices. Programmers and web developers are in need of significant research on how to successfully develop pattern recognition applications using intelligent programming. MatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition: Emerging Research and Opportunities is an essential reference source that presents a solution to developing intelligent pattern recognition Apps on iOS devices based on MatConvNet deep learning. Featuring research on topics such as medical image diagnosis, convolutional neural networks, and character classification, this book is ideally designed for programmers, developers, researchers, practitioners, engineers, academicians, students, scientists, and educators seeking coverage on the specific development of iOS mobile applications using pattern recognition strategies.

Learn iOS Application Development

Author : Rudra
Publisher : BPB Publications
Page : 606 pages
File Size : 48,6 Mb
Release : 2021-07-19
Category : Computers
ISBN : 9789390684755

Get Book

Learn iOS Application Development by Rudra Pdf

Explore the complex app development concepts for iOS application programming with fun and ease. KEY FEATURES ● In-depth knowledge with practical examples on how to develop professional iOS apps. ● Includes coverage on the entire iOS application development, right from designing the UI to application deployment. ● Get to know more about machine learning and augmented reality, and their impact on iOS apps. DESCRIPTION Grab this book if you want to make Apps for Apple’s iOS devices and that too efficiently like a skilled developer. This book covers the complete development of iOS applications, right from concepts of designing an application to adding machine learning capabilities in the applications. You will learn and practice the App development environment with Xcode and Swift programming. Concepts like different types of views and UI components, data manipulations, animations, different iOS screen views, and integrating web services are covered in detail with examples. You will also learn the popular machine learning technology and fascinating features like Augmented Reality to be put into use in your app. You will learn to run automated application testing, use SwiftUI, and deploy applications on the network. WHAT YOU WILL LEARN ● Build strong familiarity with the entire application development environment. ● Revive essential coding concepts and methods of Swift and Xcode. ● Simplify integration of iOS apps with web services, including JSON and XML decoding. ● Learn to work with iOS ARKit and add the experience of augmented reality to applications. ● Work with popular SwiftUI, XCTest, and a growing machine learning library, CoreML. WHO THIS BOOK IS FOR This book caters to mobile developers, application developers, and students who want to build sound proficiency in the entire process of iOS Application development. Knowing basic programming concepts would be good, although not mandatory. TABLE OF CONTENTS 1. iOS App Development Environment 2. Swift Programming Language 3. User Interface and Data Handling 4. Different Views in iOS Devices 5. Image and Animation 6. Multi-View Application and Navigation 7. Data Persistence for iOS Devices 8. Integration with Web Services 9. Augmented Reality 10. Machine Learning 11. App Testing and Deployment 12. SwiftUI

Deep Learning for Coders with fastai and PyTorch

Author : Jeremy Howard,Sylvain Gugger
Publisher : O'Reilly Media
Page : 624 pages
File Size : 41,9 Mb
Release : 2020-06-29
Category : Computers
ISBN : 9781492045496

Get Book

Deep Learning for Coders with fastai and PyTorch by Jeremy Howard,Sylvain Gugger Pdf

Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala

AI and Machine Learning for Coders

Author : Laurence Moroney
Publisher : O'Reilly Media
Page : 393 pages
File Size : 49,9 Mb
Release : 2020-10-01
Category : Computers
ISBN : 9781492078166

Get Book

AI and Machine Learning for Coders by Laurence Moroney Pdf

If you're looking to make a career move from programmer to AI specialist, this is the ideal place to start. Based on Laurence Moroney's extremely successful AI courses, this introductory book provides a hands-on, code-first approach to help you build confidence while you learn key topics. You'll understand how to implement the most common scenarios in machine learning, such as computer vision, natural language processing (NLP), and sequence modeling for web, mobile, cloud, and embedded runtimes. Most books on machine learning begin with a daunting amount of advanced math. This guide is built on practical lessons that let you work directly with the code. You'll learn: How to build models with TensorFlow using skills that employers desire The basics of machine learning by working with code samples How to implement computer vision, including feature detection in images How to use NLP to tokenize and sequence words and sentences Methods for embedding models in Android and iOS How to serve models over the web and in the cloud with TensorFlow Serving

AI and Machine Learning for On-Device Development

Author : Laurence Moroney
Publisher : "O'Reilly Media, Inc."
Page : 328 pages
File Size : 45,8 Mb
Release : 2021-08-12
Category : Computers
ISBN : 9781098101701

Get Book

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

AI is nothing without somewhere to run it. Now that mobile devices have become the primary computing device for most people, it's essential that mobile developers add AI to their toolbox. This insightful book is your guide to creating and running models on popular mobile platforms such as iOS and Android. Laurence Moroney, lead AI advocate at Google, offers an introduction to machine learning techniques and tools, then walks you through writing Android and iOS apps powered by common ML models like computer vision and text recognition, using tools such as ML Kit, TensorFlow Lite, and Core ML. If you're a mobile developer, this book will help you take advantage of the ML revolution today. Explore the options for implementing ML and AI on mobile devices Create ML models for iOS and Android Write ML Kit and TensorFlow Lite apps for iOS and Android, and Core ML/Create ML apps for iOS Choose the best techniques and tools for your use case, such as cloud-based versus on-device inference and high-level versus low-level APIs Learn privacy and ethics best practices for ML on devices

Learning IOS Development

Author : Maurice Sharp,Rod Strougo,Erica Sadun
Publisher : Addison-Wesley Professional
Page : 591 pages
File Size : 45,5 Mb
Release : 2014
Category : Computers
ISBN : 9780321862969

Get Book

Learning IOS Development by Maurice Sharp,Rod Strougo,Erica Sadun Pdf

This book offers the perfect hands-on introduction to iOS development, covering everything your students need to know about Objective-C, XCode, and modern iOS user interface development. With sample projects and end-of-chapter exercises, this book is ideal for classroom instruction. The authors get started fast with Objective-C, covering basic syntax, memory management, Foundation Classes, development paradigms, blocks, threads, and more. Next, they show how to use XCode and related tools to build projects, instrument and efficiently debug code, and deploy apps. In the next part, hey turn to interfaces, covering design, content construction, View Controllers, Views, Animations, Touch, Table Views, and even a taste of Core Data.