Intelligent Mobile Projects With Tensorflow
DOWNLOAD
Download Intelligent Mobile Projects With Tensorflow PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Intelligent Mobile Projects With Tensorflow book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Intelligent Mobile Projects With Tensorflow
DOWNLOAD
Author : Jeff Tang
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-05-22
Intelligent Mobile Projects With Tensorflow written by Jeff Tang 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 2018-05-22 with Computers categories.
Create Deep Learning and Reinforcement Learning apps for multiple platforms with TensorFlow Key Features Build TensorFlow-powered AI applications for mobile and embedded devices Learn modern AI topics such as computer vision, NLP, and deep reinforcement learning Get practical insights and exclusive working code not available in the TensorFlow documentation Book Description As a developer, you always need to keep an eye out and be ready for what will be trending soon, while also focusing on what's trending currently. So, what's better than learning about the integration of the best of both worlds, the present and the future? Artificial Intelligence (AI) is widely regarded as the next big thing after mobile, and Google's TensorFlow is the leading open source machine learning framework, the hottest branch of AI. This book covers more than 10 complete iOS, Android, and Raspberry Pi apps powered by TensorFlow and built from scratch, running all kinds of cool TensorFlow models offline on-device: from computer vision, speech and language processing to generative adversarial networks and AlphaZero-like deep reinforcement learning. You’ll learn how to use or retrain existing TensorFlow models, build your own models, and develop intelligent mobile apps running those TensorFlow models. You'll learn how to quickly build such apps with step-by-step tutorials and how to avoid many pitfalls in the process with lots of hard-earned troubleshooting tips. What you will learn Classify images with transfer learning Detect objects and their locations Transform pictures with amazing art styles Understand simple speech commands Describe images in natural language Recognize drawing with Convolutional Neural Network and Long Short-Term Memory Predict stock price with Recurrent Neural Network in TensorFlow and Keras Generate and enhance images with generative adversarial networks Build AlphaZero-like mobile game app in TensorFlow and Keras Use TensorFlow Lite and Core ML on mobile Develop TensorFlow apps on Raspberry Pi that can move, see, listen, speak, and learn Who this book is for If you're an iOS/Android developer interested in building and retraining others' TensorFlow models and running them in your mobile apps, or if you're a TensorFlow developer and want to run your new and amazing TensorFlow models on mobile devices, this book is for you. You'll also benefit from this book if you're interested in TensorFlow Lite, Core ML, or TensorFlow on Raspberry Pi.
Intelligent Projects Using Python
DOWNLOAD
Author : Santanu Pattanayak
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-01-31
Intelligent Projects Using Python written by Santanu Pattanayak 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 2019-01-31 with Computers categories.
Implement machine learning and deep learning methodologies to build smart, cognitive AI projects using Python Key FeaturesA go-to guide to help you master AI algorithms and concepts8 real-world projects tackling different challenges in healthcare, e-commerce, and surveillanceUse TensorFlow, Keras, and other Python libraries to implement smart AI applicationsBook Description This book will be a perfect companion if you want to build insightful projects from leading AI domains using Python. The book covers detailed implementation of projects from all the core disciplines of AI. We start by covering the basics of how to create smart systems using machine learning and deep learning techniques. You will assimilate various neural network architectures such as CNN, RNN, LSTM, to solve critical new world challenges. You will learn to train a model to detect diabetic retinopathy conditions in the human eye and create an intelligent system for performing a video-to-text translation. You will use the transfer learning technique in the healthcare domain and implement style transfer using GANs. Later you will learn to build AI-based recommendation systems, a mobile app for sentiment analysis and a powerful chatbot for carrying customer services. You will implement AI techniques in the cybersecurity domain to generate Captchas. Later you will train and build autonomous vehicles to self-drive using reinforcement learning. You will be using libraries from the Python ecosystem such as TensorFlow, Keras and more to bring the core aspects of machine learning, deep learning, and AI. By the end of this book, you will be skilled to build your own smart models for tackling any kind of AI problems without any hassle. What you will learnBuild an intelligent machine translation system using seq-2-seq neural translation machinesCreate AI applications using GAN and deploy smart mobile apps using TensorFlowTranslate videos into text using CNN and RNNImplement smart AI Chatbots, and integrate and extend them in several domainsCreate smart reinforcement, learning-based applications using Q-LearningBreak and generate CAPTCHA using Deep Learning and Adversarial Learning Who this book is for This book is intended for data scientists, machine learning professionals, and deep learning practitioners who are ready to extend their knowledge and potential in AI. If you want to build real-life smart systems to play a crucial role in every complex domain, then this book is what you need. Knowledge of Python programming and a familiarity with basic machine learning and deep learning concepts are expected to help you get the most out of the book
Mobile Deep Learning With Tensorflow Lite Ml Kit And Flutter
DOWNLOAD
Author : Anubhav Singh
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-04-06
Mobile Deep Learning With Tensorflow Lite Ml Kit And Flutter written by Anubhav Singh 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 2020-04-06 with Computers categories.
Learn how to deploy effective deep learning solutions on cross-platform applications built using TensorFlow Lite, ML Kit, and Flutter Key FeaturesWork through projects covering mobile vision, style transfer, speech processing, and multimedia processingCover interesting deep learning solutions for mobileBuild your confidence in training models, performance tuning, memory optimization, and neural network deployment through every projectBook Description Deep learning is rapidly becoming the most popular topic in the mobile app industry. This book introduces trending deep learning concepts and their use cases with an industrial and application-focused approach. You will cover a range of projects covering tasks such as mobile vision, facial recognition, smart artificial intelligence assistant, augmented reality, and more. With the help of eight projects, you will learn how to integrate deep learning processes into mobile platforms, iOS, and Android. This will help you to transform deep learning features into robust mobile apps efficiently. You’ll get hands-on experience of selecting the right deep learning architectures and optimizing mobile deep learning models while following an application oriented-approach to deep learning on native mobile apps. We will later cover various pre-trained and custom-built deep learning model-based APIs such as machine learning (ML) Kit through Firebase. Further on, the book will take you through examples of creating custom deep learning models with TensorFlow Lite. Each project will demonstrate how to integrate deep learning libraries into your mobile apps, right from preparing the model through to deployment. By the end of this book, you’ll have mastered the skills to build and deploy deep learning mobile applications on both iOS and Android. What you will learnCreate your own customized chatbot by extending the functionality of Google AssistantImprove learning accuracy with the help of features available on mobile devicesPerform visual recognition tasks using image processingUse augmented reality to generate captions for a camera feedAuthenticate users and create a mechanism to identify rare and suspicious user interactionsDevelop a chess engine based on deep reinforcement learningExplore the concepts and methods involved in rolling out production-ready deep learning iOS and Android applicationsWho this book is for This book is for data scientists, deep learning and computer vision engineers, and natural language processing (NLP) engineers who want to build smart mobile apps using deep learning methods. You will also find this book useful if you want to improve your mobile app’s user interface (UI) by harnessing the potential of deep learning. Basic knowledge of neural networks and coding experience in Python will be beneficial to get started with this book.
Machine Learning Projects For Mobile Applications
DOWNLOAD
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.
Mobile Artificial Intelligence Projects
DOWNLOAD
Author : Karthikeyan NG
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-03-30
Mobile Artificial Intelligence Projects 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 2019-03-30 with Computers categories.
Learn to build end-to-end AI apps from scratch for Android and iOS using TensorFlow Lite, CoreML, and PyTorch Key FeaturesBuild practical, real-world AI projects on Android and iOSImplement tasks such as recognizing handwritten digits, sentiment analysis, and moreExplore the core functions of machine learning, deep learning, and mobile visionBook Description We’re witnessing a revolution in Artificial Intelligence, thanks to breakthroughs in deep learning. Mobile Artificial Intelligence Projects empowers you to take part in this revolution by applying Artificial Intelligence (AI) techniques to design applications for natural language processing (NLP), robotics, and computer vision. This book teaches you to harness the power of AI in mobile applications along with learning the core functions of NLP, neural networks, deep learning, and mobile vision. It features a range of projects, covering tasks such as real-estate price prediction, recognizing hand-written digits, predicting car damage, and sentiment analysis. You will learn to utilize NLP and machine learning algorithms to make applications more predictive, proactive, and capable of making autonomous decisions with less human input. In the concluding chapters, you will work with popular libraries, such as TensorFlow Lite, CoreML, and PyTorch across Android and iOS platforms. By the end of this book, you will have developed exciting and more intuitive mobile applications that deliver a customized and more personalized experience to users. What you will learnExplore the concepts and fundamentals of AI, deep learning, and neural networksImplement use cases for machine vision and natural language processingBuild an ML model to predict car damage using TensorFlowDeploy TensorFlow on mobile to convert speech to textImplement GAN to recognize hand-written digitsDevelop end-to-end mobile applications that use AI principlesWork with popular libraries, such as TensorFlow Lite, CoreML, and PyTorchWho this book is for Mobile Artificial Intelligence Projects is for machine learning professionals, deep learning engineers, AI engineers, and software engineers who want to integrate AI technology into mobile-based platforms and applications. Sound knowledge of machine learning and experience with any programming language is all you need to get started with this book.
Hands On Tensorflow Lite For Intelligent Mobile Apps
DOWNLOAD
Author : Juan Martinez
language : en
Publisher:
Release Date : 2018
Hands On Tensorflow Lite For Intelligent Mobile Apps written by Juan Martinez and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Internet videos categories.
"This complete guide will teach you how to build and deploy Machine Learning models on your mobile device with TensorFlow Lite. You will understand the core architecture of TensorFlow Lite and the inbuilt models that have been optimized for mobiles. You will learn to implement smart data-intensive behavior, fast, predictive algorithms, and efficient networking capabilities with TensorFlow Lite. You will master the TensorFlow Lite Converter, which converts models to the TensorFlow Lite file format. This course will teach you how to solve real-life problems related to Artificial Intelligence--such as image, text, and voice recognition--by developing models in TensorFlow to make your applications really smart. You will understand what Machine Learning can do for you and your mobile applications in the most efficient way. With the capabilities of TensorFlow Lite you will learn to improve the performance of your mobile application and make it smart."--Resource description page.
Machine Learning For Mobile
DOWNLOAD
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
Hands On Tensorflow Lite For Intelligent Mobile Apps
DOWNLOAD
Author : Juan Miguel Valverde Martinez
language : en
Publisher:
Release Date : 2018
Hands On Tensorflow Lite For Intelligent Mobile Apps written by Juan Miguel Valverde Martinez and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
"This complete guide will teach you how to build and deploy Machine Learning models on your mobile device with TensorFlow Lite. You will understand the core architecture of TensorFlow Lite and the inbuilt models that have been optimized for mobiles. You will learn to implement smart data-intensive behavior, fast, predictive algorithms, and efficient networking capabilities with TensorFlow Lite. You will master the TensorFlow Lite Converter, which converts models to the TensorFlow Lite file format. This course will teach you how to solve real-life problems related to Artificial Intelligence--such as image, text, and voice recognition--by developing models in TensorFlow to make your applications really smart. You will understand what Machine Learning can do for you and your mobile applications in the most efficient way. With the capabilities of TensorFlow Lite you will learn to improve the performance of your mobile application and make it smart."--Resource description page.
Machine Learning And Deep Learning Using Python And Tensorflow
DOWNLOAD
Author : Venkata Reddy Konasani
language : en
Publisher: McGraw Hill Professional
Release Date : 2021-04-29
Machine Learning And Deep Learning Using Python And Tensorflow written by Venkata Reddy Konasani and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-29 with Technology & Engineering categories.
Understand the principles and practices of machine learning and deep learning This hands-on guide lays out machine learning and deep learning techniques and technologies in a style that is approachable, using just the basic math required. Written by a pair of experts in the field, Machine Learning and Deep Learning Using Python and TensorFlow contains case studies in several industries, including banking, insurance, e-commerce, retail, and healthcare. The book shows how to utilize machine learning and deep learning functions in today’s smart devices and apps. You will get download links for datasets, code, and sample projects referred to in the text. Coverage includes: Machine learning and deep learning concepts Python programming and statistics fundamentals Regression and logistic regression Decision trees Model selection and cross-validation Cluster analysis Random forests and boosting Artificial neural networks TensorFlow and Keras Deep learning hyperparameters Convolutional neural networks Recurrent neural networks and long short-term memory
Deep Learning With Tensorflow
DOWNLOAD
Author : Giancarlo Zaccone
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-03-30
Deep Learning With Tensorflow written by Giancarlo Zaccone 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 2018-03-30 with Computers categories.
Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of TensorFlow. Key Features Learn how to implement advanced techniques in deep learning with Google's brainchild, TensorFlow Explore deep neural networks and layers of data abstraction with the help of this comprehensive guide Gain real-world contextualization through some deep learning problems concerning research and application Book Description Deep learning is a branch of machine learning algorithms based on learning multiple levels of abstraction. Neural networks, which are at the core of deep learning, are being used in predictive analytics, computer vision, natural language processing, time series forecasting, and to perform a myriad of other complex tasks. This book is conceived for developers, data analysts, machine learning practitioners and deep learning enthusiasts who want to build powerful, robust, and accurate predictive models with the power of TensorFlow, combined with other open source Python libraries. Throughout the book, you’ll learn how to develop deep learning applications for machine learning systems using Feedforward Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Autoencoders, and Factorization Machines. Discover how to attain deep learning programming on GPU in a distributed way. You'll come away with an in-depth knowledge of machine learning techniques and the skills to apply them to real-world projects. What you will learn Apply deep machine intelligence and GPU computing with TensorFlow Access public datasets and use TensorFlow to load, process, and transform the data Discover how to use the high-level TensorFlow API to build more powerful applications Use deep learning for scalable object detection and mobile computing Train machines quickly to learn from data by exploring reinforcement learning techniques Explore active areas of deep learning research and applications Who this book is for The book is for people interested in machine learning and machine intelligence. A rudimentary level of programming in one language is assumed, as is a basic familiarity with computer science techniques and technologies, including a basic awareness of computer hardware and algorithms. Some competence in mathematics is needed to the level of elementary linear algebra and calculus.