Mastering Machine Learning With Core Ml And Python
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Mastering Machine Learning With Core Ml And Python
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Author : Vardhan Agrawal
language : en
Publisher: AppCoda
Release Date : 2020-08-13
Mastering Machine Learning With Core Ml And Python written by Vardhan Agrawal and has been published by AppCoda this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-13 with Computers categories.
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
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Author : Joshua Newnham
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-06-28
Machine Learning With Core Ml written by Joshua Newnham and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-28 with Computers categories.
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 Projects For Mobile Applications
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Author : Karthikeyan NG
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-10-31
Machine Learning Projects For Mobile Applications written by Karthikeyan NG and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-31 with Computers categories.
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.
Mastering Machine Learning With Python In Six Steps
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Author : Manohar Swamynathan
language : en
Publisher: Apress
Release Date : 2019-10-01
Mastering Machine Learning With Python In Six Steps written by Manohar Swamynathan and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-01 with Computers categories.
Explore fundamental to advanced Python 3 topics in six steps, all designed to make you a worthy practitioner. This updated version’s approach is based on the “six degrees of separation” theory, which states that everyone and everything is a maximum of six steps away and presents each topic in two parts: theoretical concepts and practical implementation using suitable Python 3 packages. You’ll start with the fundamentals of Python 3 programming language, machine learning history, evolution, and the system development frameworks. Key data mining/analysis concepts, such as exploratory analysis, feature dimension reduction, regressions, time series forecasting and their efficient implementation in Scikit-learn are covered as well. You’ll also learn commonly used model diagnostic and tuning techniques. These include optimal probability cutoff point for class creation, variance, bias, bagging, boosting, ensemble voting, grid search, random search, Bayesian optimization, and the noise reduction technique for IoT data. Finally, you’ll review advanced text mining techniques, recommender systems, neural networks, deep learning, reinforcement learning techniques and their implementation. All the code presented in the book will be available in the form of iPython notebooks to enable you to try out these examples and extend them to your advantage. What You'll Learn Understand machine learning development and frameworks Assess model diagnosis and tuning in machine learning Examine text mining, natuarl language processing (NLP), and recommender systems Review reinforcement learning and CNN Who This Book Is For Python developers, data engineers, and machine learning engineers looking to expand their knowledge or career into machine learning area.
Practical Deep Learning For Cloud Mobile And Edge
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Author : Anirudh Koul
language : en
Publisher: O'Reilly Media
Release Date : 2019-10-14
Practical Deep Learning For Cloud Mobile And Edge written by Anirudh Koul and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-14 with Computers categories.
Whether you’re a software engineer aspiring to enter the world of deep learning, a veteran data scientist, or a hobbyist with a simple dream of making the next viral AI app, you might have wondered where to begin. This step-by-step guide teaches you how to build practical deep learning applications for the cloud, mobile, browsers, and edge devices using a hands-on approach. Relying on years of industry experience transforming deep learning research into award-winning applications, Anirudh Koul, Siddha Ganju, and Meher Kasam guide you through the process of converting an idea into something that people in the real world can use. Train, tune, and deploy computer vision models with Keras, TensorFlow, Core ML, and TensorFlow Lite Develop AI for a range of devices including Raspberry Pi, Jetson Nano, and Google Coral Explore fun projects, from Silicon Valley’s Not Hotdog app to 40+ industry case studies Simulate an autonomous car in a video game environment and build a miniature version with reinforcement learning Use transfer learning to train models in minutes Discover 50+ practical tips for maximizing model accuracy and speed, debugging, and scaling to millions of users
Mastering Python 3 Programming
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Author : Subburaj Ramasamy
language : en
Publisher: BPB Publications
Release Date : 2024-05-14
Mastering Python 3 Programming written by Subburaj Ramasamy and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-14 with Computers categories.
Learn the nitty-gritty of Python 3 programming language by coding and executing programs seamlessly in a lucid manner KEY FEATURES ● Python 3 fundamentals, from data manipulation to control flow. ● Key concepts like data structures, algorithms, and Python applications, catering to a diverse audience. ● Beginner-friendly guide with step-by-step explanations and practical examples. DESCRIPTION Python 3's clear and concise syntax and extensive collection of built-in libraries and frameworks make it a powerful and versatile programming language. This comprehensive guide, "Mastering Python 3 Programming", is designed to take you from the ground up to proficiency, equipping you to create effective Python programs. This book provides an extensive overview of Python programming, covering a diverse range of topics essential for understanding Python 3. Each chapter explores key concepts like Unicode strings, functions and recursions, lists, tuples, sets, and dictionaries, along with advanced topics such as object-oriented programming, file handling, exception handling, and more. With detailed explanations and real-life examples, you will be able to build a strong understanding of Python 3. Throughout the book, you will find useful concepts and Python libraries explained clearly, along with case studies, executable programs, exercises, and easy-to-follow style. This book focuses on real-world Python applications, developing critical thinking and problem-solving skills. It prepares students for Python challenges, equipping them to contribute meaningfully in their fields. With a deep understanding of Python, students gain confidence to explore new opportunities and drive innovation. WHAT YOU WILL LEARN ● Set up IDLE for Python programming and execute programs. ● Adapt algorithm based problem-solving techniques. ● Utilize Python libraries for data visualization. ● Grasp data structures and common algorithms. ● Master decorators, file handling, exception handling, inheritance, polymorphism, and recursion in Python. WHO THIS BOOK IS FOR The target audience for this book includes undergraduate students from diverse academic backgrounds, including life sciences, mathematics, commerce, management, arts, and individuals who are new to computer science. TABLE OF CONTENTS 1. Introduction to Python 3 2. Algorithmic Problem Solving 3. Numeric Computations and Console Input 4. Unicode, Strings and Console Output 5. Selection and Loops 6. Functions and Recursion 7. Lists 8. Tuples, Sets, and Dictionaries 9. Introduction to Object-Oriented Programming 10. Inheritance and Polymorphism 11. File Handling 12. Exception Handling 13. Gems of Python 14. Data Structures and Algorithms using Python 15. Data Visualization 16. Python Applications and Libraries Appendix 1: Python Projects Appendix 2: List of Built-in Functions in Python Appendix 3: Answers to Review Questions
Mastering Ios 14 Programming
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Author : Mario Eguiluz Alebicto
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-03-19
Mastering Ios 14 Programming written by Mario Eguiluz Alebicto and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-19 with Computers categories.
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.
Advanced Machine Learning With Python
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Author : John Hearty
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-07-28
Advanced Machine Learning With Python written by John Hearty and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-28 with Computers categories.
Solve challenging data science problems by mastering cutting-edge machine learning techniques in Python About This Book Resolve complex machine learning problems and explore deep learning Learn to use Python code for implementing a range of machine learning algorithms and techniques A practical tutorial that tackles real-world computing problems through a rigorous and effective approach Who This Book Is For This title is for Python developers and analysts or data scientists who are looking to add to their existing skills by accessing some of the most powerful recent trends in data science. If you've ever considered building your own image or text-tagging solution, or of entering a Kaggle contest for instance, this book is for you! Prior experience of Python and grounding in some of the core concepts of machine learning would be helpful. What You Will Learn Compete with top data scientists by gaining a practical and theoretical understanding of cutting-edge deep learning algorithms Apply your new found skills to solve real problems, through clearly-explained code for every technique and test Automate large sets of complex data and overcome time-consuming practical challenges Improve the accuracy of models and your existing input data using powerful feature engineering techniques Use multiple learning techniques together to improve the consistency of results Understand the hidden structure of datasets using a range of unsupervised techniques Gain insight into how the experts solve challenging data problems with an effective, iterative, and validation-focused approach Improve the effectiveness of your deep learning models further by using powerful ensembling techniques to strap multiple models together In Detail Designed to take you on a guided tour of the most relevant and powerful machine learning techniques in use today by top data scientists, this book is just what you need to push your Python algorithms to maximum potential. Clear examples and detailed code samples demonstrate deep learning techniques, semi-supervised learning, and more - all whilst working with real-world applications that include image, music, text, and financial data. The machine learning techniques covered in this book are at the forefront of commercial practice. They are applicable now for the first time in contexts such as image recognition, NLP and web search, computational creativity, and commercial/financial data modeling. Deep Learning algorithms and ensembles of models are in use by data scientists at top tech and digital companies, but the skills needed to apply them successfully, while in high demand, are still scarce. This book is designed to take the reader on a guided tour of the most relevant and powerful machine learning techniques. Clear descriptions of how techniques work and detailed code examples demonstrate deep learning techniques, semi-supervised learning and more, in real world applications. We will also learn about NumPy and Theano. By this end of this book, you will learn a set of advanced Machine Learning techniques and acquire a broad set of powerful skills in the area of feature selection & feature engineering. Style and approach This book focuses on clarifying the theory and code behind complex algorithms to make them practical, useable, and well-understood. Each topic is described with real-world applications, providing both broad contextual coverage and detailed guidance.
Machine Learning For Mobile
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Author : Revathi Gopalakrishnan
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-12-31
Machine Learning For Mobile written by Revathi Gopalakrishnan and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-31 with Computers categories.
Leverage the power of machine learning on mobiles and build intelligent mobile applications with ease Key FeaturesBuild smart mobile applications for Android and iOS devicesUse popular machine learning toolkits such as Core ML and TensorFlow LiteExplore cloud services for machine learning that can be used in mobile appsBook Description Machine learning presents an entirely unique opportunity in software development. It allows smartphones to produce an enormous amount of useful data that can be mined, analyzed, and used to make predictions. This book will help you master machine learning for mobile devices with easy-to-follow, practical examples. You will begin with an introduction to machine learning on mobiles and grasp the fundamentals so you become well-acquainted with the subject. You will master supervised and unsupervised learning algorithms, and then learn how to build a machine learning model using mobile-based libraries such as Core ML, TensorFlow Lite, ML Kit, and Fritz on Android and iOS platforms. In doing so, you will also tackle some common and not-so-common machine learning problems with regard to Computer Vision and other real-world domains. By the end of this book, you will have explored machine learning in depth and implemented on-device machine learning with ease, thereby gaining a thorough understanding of how to run, create, and build real-time machine-learning applications on your mobile devices. What you will learnBuild intelligent machine learning models that run on Android and iOSUse machine learning toolkits such as Core ML, TensorFlow Lite, and moreLearn how to use Google Mobile Vision in your mobile appsBuild a spam message detection system using Linear SVMUsing Core ML to implement a regression model for iOS devicesBuild image classification systems using TensorFlow Lite and Core MLWho this book is for If you are a mobile app developer or a machine learning enthusiast keen to use machine learning to build smart mobile applications, this book is for you. Some experience with mobile application development is all you need to get started with this book. Prior experience with machine learning will be an added bonus
Machine Learning For Ios Developers
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Author : Abhishek Mishra
language : en
Publisher: John Wiley & Sons
Release Date : 2020-02-12
Machine Learning For Ios Developers written by Abhishek Mishra and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-12 with Computers categories.
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.