Beginning Machine Learning In Ios

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Machine Learning by Tutorials (Second Edition)

Author : raywenderlich Tutorial Team
Publisher :
ISBN 13 : 9781942878933
Total Pages : pages
Book Rating : 4.8/5 (789 download)

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Book Synopsis Machine Learning by Tutorials (Second Edition) by : raywenderlich Tutorial Team

Download or read book Machine Learning by Tutorials (Second Edition) written by raywenderlich Tutorial Team and published by . This book was released on 2020-05-19 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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!

Beginning Machine Learning in iOS

Author : Mohit Thakkar
Publisher : Apress
ISBN 13 : 1484242971
Total Pages : 163 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Beginning Machine Learning in iOS by : Mohit Thakkar

Download or read book Beginning Machine Learning in iOS written by Mohit Thakkar and published by Apress. This book was released on 2019-02-20 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Machine Learning with Core ML

Author : Joshua Newnham
Publisher : Packt Publishing Ltd
ISBN 13 : 178883559X
Total Pages : 368 pages
Book Rating : 4.7/5 (888 download)

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Book Synopsis Machine Learning with Core ML by : Joshua Newnham

Download or read book Machine Learning with Core ML written by Joshua Newnham and published by Packt Publishing Ltd. This book was released on 2018-06-28 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 with Swift

Author : Oleksandr Sosnovshchenko
Publisher : Packt Publishing Ltd
ISBN 13 : 1787123529
Total Pages : 371 pages
Book Rating : 4.7/5 (871 download)

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Book Synopsis Machine Learning with Swift by : Oleksandr Sosnovshchenko

Download or read book Machine Learning with Swift written by Oleksandr Sosnovshchenko and published by Packt Publishing Ltd. This book was released on 2018-02-28 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Machine Learning for iOS Developers

Author : Abhishek Mishra
Publisher : John Wiley & Sons
ISBN 13 : 1119602874
Total Pages : 352 pages
Book Rating : 4.1/5 (196 download)

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Book Synopsis Machine Learning for iOS Developers by : Abhishek Mishra

Download or read book Machine Learning for iOS Developers written by Abhishek Mishra and published by John Wiley & Sons. This book was released on 2020-03-04 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Projects for Mobile Applications

Author : Karthikeyan NG
Publisher : Packt Publishing Ltd
ISBN 13 : 1788998464
Total Pages : 240 pages
Book Rating : 4.7/5 (889 download)

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Book Synopsis Machine Learning Projects for Mobile Applications by : Karthikeyan NG

Download or read book Machine Learning Projects for Mobile Applications written by Karthikeyan NG and published by Packt Publishing Ltd. This book was released on 2018-10-31 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Deep Learning for Coders with fastai and PyTorch

Author : Jeremy Howard
Publisher : O'Reilly Media
ISBN 13 : 1492045497
Total Pages : 624 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Deep Learning for Coders with fastai and PyTorch by : Jeremy Howard

Download or read book Deep Learning for Coders with fastai and PyTorch written by Jeremy Howard and published by O'Reilly Media. This book was released on 2020-06-29 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Mastering Machine Learning with Core ML and Python

Author : Vardhan Agrawal
Publisher : AppCoda
ISBN 13 : 9887535001
Total Pages : 330 pages
Book Rating : 4.8/5 (875 download)

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Book Synopsis Mastering Machine Learning with Core ML and Python by : Vardhan Agrawal

Download or read book Mastering Machine Learning with Core ML and Python written by Vardhan Agrawal and published by AppCoda. This book was released on 2020-08-13 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

AI and Machine Learning for On-Device Development

Author : Laurence Moroney
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1098101715
Total Pages : 329 pages
Book Rating : 4.0/5 (981 download)

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Book Synopsis AI and Machine Learning for On-Device Development by : Laurence Moroney

Download or read book AI and Machine Learning for On-Device Development written by Laurence Moroney and published by "O'Reilly Media, Inc.". This book was released on 2021-08-12 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 with Core ML 2 and Swift

Author : Karoly Nyisztor
Publisher : Independently Published
ISBN 13 : 9781983292064
Total Pages : 154 pages
Book Rating : 4.2/5 (92 download)

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Book Synopsis Machine Learning with Core ML 2 and Swift by : Karoly Nyisztor

Download or read book Machine Learning with Core ML 2 and Swift written by Karoly Nyisztor and published by Independently Published. This book was released on 2018-10-21 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Image Processing and Computer Vision in iOS

Author : Oge Marques
Publisher : Springer Nature
ISBN 13 : 3030540324
Total Pages : 66 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Image Processing and Computer Vision in iOS by : Oge Marques

Download or read book Image Processing and Computer Vision in iOS written by Oge Marques and published by Springer Nature. This book was released on 2020-11-23 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Exploring Machine Learning: A Beginners Perspective

Author : Dr. Raghuram Bhukya
Publisher : Horizon Books ( A Division of Ignited Minds Edutech P Ltd)
ISBN 13 : 9391150012
Total Pages : pages
Book Rating : 4.3/5 (911 download)

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Book Synopsis Exploring Machine Learning: A Beginners Perspective by : Dr. Raghuram Bhukya

Download or read book Exploring Machine Learning: A Beginners Perspective written by Dr. Raghuram Bhukya and published by Horizon Books ( A Division of Ignited Minds Edutech P Ltd). This book was released on 2021-04-20 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning is a field of Artificial intelligence that provides algorithms those can learn and improve from experiences. Machine learning algorithms are turned as integral parts of today’s digital life. Its applications include recommender systems, targeted campaigns, text categorization, computer vision and auto security systems etc. Machine learning also considered as essential part of data science due to its capability of providing predictive analytics, capability in handling variety of data and suitability for big data applications. Its capability for predictive analytics resulted of its general structure that is building statistical models out of training data. In other hand easy scalability advantage of machine learning algorithms is making them to be suitable for big data applications. The different types of learning algorithms includes supervised learning, unsupervised learning, reinforcement learning, feature learning, rule based learning, Robot or expert system learning, sparse dictionary and anomaly detection. These learning algorithms can be realized by computing models artificial neural networks, decision trees, support vector machines, regression analysis, Bayesian networks, Genetic algorithms and soft computing. The familiar tools to implement machine learning algorithms include Python, R, Matlab, Scala, Clojure and Ruby. Involving of such open source programming languages, tools and social network communities makes the machine learning most progressing filed of computer science. The machine learning life cycle includes defining project objectives, explore the types and format, modeling data to fit for machine learning algorithms, deciding suitable machine learning model and implement and decide best result from data for decision making. These days, machine learning is observing great interest by the society and it has turned as one of the significant responsibility of top level managers to transform their business in the profitable means by exploring its basic functionalities. The world is at the sheer of realizing a situation where machines will work in agreement with human being to work together, operation, and advertise their services in a novel way which is targeted, valuable, and well-versed. In order to achieve this, they can influence machine learning distinctiveness. Dr. Raghuram Bhukya

iOS 17 App Development for Beginners

Author : Arpit Kulsreshtha
Publisher : BPB Publications
ISBN 13 : 9355515855
Total Pages : 538 pages
Book Rating : 4.3/5 (555 download)

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Book Synopsis iOS 17 App Development for Beginners by : Arpit Kulsreshtha

Download or read book iOS 17 App Development for Beginners written by Arpit Kulsreshtha and published by BPB Publications. This book was released on 2023-10-10 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn iOS app development from scratch and build your dream app KEY FEATURES ● Experience the cutting-edge capabilities of Xcode 15 and Swift 5.9 with this enhanced edition, unraveling the latest features. ● Embark on an exciting journey into the world of iOS programming while enjoying the process of building your very own iOS apps. ● Uncover the exciting advancements in iOS 17, including SwiftData, ActivityKit, SwiftUI, CoreML, and the Symbol Framework. DESCRIPTION “iOS 17 App Development for Beginners” is a definitive guide to building iOS apps with Swift. This book teaches the fundamentals of Swift, laying the foundation for future app development. It covers how to develop user interfaces for iOS apps using SwiftUI and UIKit and how to write code for views, view controllers, and data managers. The book also teaches using Core Data, Swift Data, and SQLite for database storage. Additionally, it covers essential Apple technologies and frameworks, such as Core Location and MapKit for GPS tracking, Camera and Photo Library for image storage, CI/CD, and Core ML for machine learning and artificial intelligence solutions. After completing this book, you will have a solid grasp of Swift app development and successfully publish your apps to the App Store. WHAT YOU WILL LEARN ● Explore the enhancements in the Swift programming language. ● Discover how to seamlessly integrate and manage complex data models using SwiftData and Core Data. ● Take a deep dive into the declarative and intuitive SwiftUI framework. ● Learn how to integrate machine learning with Core ML into your apps. ● Integrate ActivityKit to create engaging and interactive experiences within your iOS 17 apps. WHO THIS BOOK IS FOR This book is an excellent resource for anyone who wants to learn how to program in Swift and develop applications for the iOS platform. Whether you are a beginner, a student, or a professional, this book will teach you the basics of Swift and how to use it to create your apps. No prior programming experience is necessary, but some familiarity with other programming languages will be helpful. TABLE OF CONTENTS 1. Getting Started with Xcode 2. Swift Fundamentals 3. Class, Structure, and Enumerations 4. Protocols, Extensions, and Error Handling 5. Automatic Reference Counting and Memory Safety 6. Implementing iOS 17 Architecture 7. User Interface Design with UIKit 8. User Interface Design with SwiftUI 9. Concurrency in Swift and SwiftUI 10. Storing Data with SQLite and Core Data 11. File Handling in iOS 12. Core Location with MapKit 13. Camera and Photo Library 14. Multithreading in iOS 15. Networking in iOS Apps 16. Mobile App Architectures, Patterns, and Anti-Patterns 17. Publish iOS App on the Apple App Store 18. Continuous Integration and Delivery with Xcode Cloud 19. Advance iOS with New Frameworks

Machine Learning for iOS Developers

Author : Abhishek Mishra
Publisher : John Wiley & Sons
ISBN 13 : 1119602912
Total Pages : 353 pages
Book Rating : 4.1/5 (196 download)

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Book Synopsis Machine Learning for iOS Developers by : Abhishek Mishra

Download or read book Machine Learning for iOS Developers written by Abhishek Mishra and published by John Wiley & Sons. This book was released on 2020-02-12 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Tracking and Preventing Diseases with Artificial Intelligence

Author : Mayuri Mehta
Publisher : Springer Nature
ISBN 13 : 3030767329
Total Pages : 266 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Tracking and Preventing Diseases with Artificial Intelligence by : Mayuri Mehta

Download or read book Tracking and Preventing Diseases with Artificial Intelligence written by Mayuri Mehta and published by Springer Nature. This book was released on 2021 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents an overview of how machine learning and data mining techniques are used for tracking and preventing diseases. It covers several aspects such as stress level identification of a person from his/her speech, automatic diagnosis of disease from X-ray images, intelligent diagnosis of Glaucoma from clinical eye examination data, prediction of protein-coding genes from big genome data, disease detection through microscopic analysis of blood cells, information retrieval from electronic medical record using named entity recognition approaches, and prediction of drug-target interactions. The book is suitable for computer scientists having a bachelor degree in computer science. The book is an ideal resource as a reference book for teaching a graduate course on AI for Medicine or AI for Health care. Researchers working in the multidisciplinary areas use this book to discover the current developments. Besides its use in academia, this book provides enough details about the state-of-the-art algorithms addressing various biomedical domains, so that it could be used by industry practitioners who want to implement AI techniques to analyze the diseases. Medical institutions use this book as reference material and give tutorials to medical experts on how the advanced AI and ML techniques contribute to the diagnosis and prediction of the diseases.

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

Author : Wu, Jiann-Ming
Publisher : IGI Global
ISBN 13 : 1799815560
Total Pages : 181 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis MatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition: Emerging Research and Opportunities by : Wu, Jiann-Ming

Download or read book MatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition: Emerging Research and Opportunities written by Wu, Jiann-Ming and published by IGI Global. This book was released on 2020-04-17 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

iOS 15 Application Development for Beginners

Author : Arpit Kulsreshtha
Publisher : BPB Publications
ISBN 13 : 9355511108
Total Pages : 382 pages
Book Rating : 4.3/5 (555 download)

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Book Synopsis iOS 15 Application Development for Beginners by : Arpit Kulsreshtha

Download or read book iOS 15 Application Development for Beginners written by Arpit Kulsreshtha and published by BPB Publications. This book was released on 2021-12-31 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn iOS App development with advanced Apple technology and developer-centric tools. KEY FEATURES ● Loaded with core developer tools, including SwiftUI, Xcode, and CoreML. ● Covers app architecture, design patterns, and mobile hardware use in app development. ● Numerous examples covering database, GPS, image recognition, and ML. DESCRIPTION This book is a step-by-step, hands-on guide for Apple developers to build iOS apps using Swift programming with minimal effort. This book will help develop the knowledge and skills necessary to program Apple applications independently. This book introduces you to Swift, SwiftUI, MapKit, Xcode, and Core ML and guides you through the process of creating a strong, marketable iOS application. The book begins with the fundamentals of Swift, which will serve as the foundation for future app development. This book will help readers to develop user interfaces for iOS applications, using SwiftUI and Interface Builder, as well as the code for views, view controllers, and data managers. The book teaches how to use Core Data and SQLite to store databases. It will help you work with Apple technologies and frameworks, including Core Location and MapKit for GPS tracking, Camera and Photo Library for image storage, Core ML for machine learning, and implementations of artificial intelligence solutions. By the end of this book, you will have developed a solid foundation for writing Swift apps, utilizing best practices in architecture, and publishing them to the app store. The book successfully introduces you to the entire iOS application development journey in a manageable manner and instills an understanding of Apple apps. WHAT YOU WILL LEARN ● Develop practical skills in Swift programming, Xcode, and SwiftUI. ● Learn to work around the database, file handling, and networking while building apps. ● Utilize the capabilities of mobile hardware to include sound, images, and videos. ● Bring machine learning capabilities using the Core ML framework. ● Integrate features such as App Gestures and Core Location into iOS applications. ● Utilize mobile design patterns and maintain a clean coding style. WHO THIS BOOK IS FOR This book is ideal for beginners in programming, students, and professionals interested in learning how to program in iOS, use various developer tools, and create Apple apps. Working knowledge of any programming language is an advantage but not required. TABLE OF CONTENTS 1. Getting Started with Xcode 2. Swift Fundamentals 3. Classes, Struct, and Enumerations 4. Protocols, Extensions, and Error Handling 5. TabBar, TableView, and CollectionView 6. User Interface Design with SwiftUI 7. Database with SQLite and Core Data 8. File Handling in iOS 9. App Gesture Recognizers in iOS 10. Core Location with MapKit 11. Camera And Photo Library 12. Machine Learning with Core ML 13. Networking in iOS Apps 14. Mobile App Patterns and Architectures 15. Publish iOS App on App Store