Go Machine Learning Projects
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Go Machine Learning Projects
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Author : Xuanyi Chew
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-11-30
Go Machine Learning Projects written by Xuanyi Chew 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 2018-11-30 with Mathematics categories.
Work through exciting projects to explore the capabilities of Go and Machine Learning Key FeaturesExplore ML tasks and Go’s machine learning ecosystemImplement clustering, regression, classification, and neural networks with GoGet to grips with libraries such as Gorgonia, Gonum, and GoCv for training models in GoBook Description Go is the perfect language for machine learning; it helps to clearly describe complex algorithms, and also helps developers to understand how to run efficient optimized code. This book will teach you how to implement machine learning in Go to make programs that are easy to deploy and code that is not only easy to understand and debug, but also to have its performance measured. The book begins by guiding you through setting up your machine learning environment with Go libraries and capabilities. You will then plunge into regression analysis of a real-life house pricing dataset and build a classification model in Go to classify emails as spam or ham. Using Gonum, Gorgonia, and STL, you will explore time series analysis along with decomposition and clean up your personal Twitter timeline by clustering tweets. In addition to this, you will learn how to recognize handwriting using neural networks and convolutional neural networks. Lastly, you'll learn how to choose the most appropriate machine learning algorithms to use for your projects with the help of a facial detection project. By the end of this book, you will have developed a solid machine learning mindset, a strong hold on the powerful Go toolkit, and a sound understanding of the practical implementations of machine learning algorithms in real-world projects. What you will learnSet up a machine learning environment with Go librariesUse Gonum to perform regression and classificationExplore time series models and decompose trends with Go librariesClean up your Twitter timeline by clustering tweetsLearn to use external services for your machine learning needsRecognize handwriting using neural networks and CNN with GorgoniaImplement facial recognition using GoCV and OpenCVWho this book is for If you’re a machine learning engineer, data science professional, or Go programmer who wants to implement machine learning in your real-world projects and make smarter applications easily, this book is for you. Some coding experience in Golang and knowledge of basic machine learning concepts will help you in understanding the concepts covered in this book.
Hands On System Programming With Go
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Author : Alex Guerrieri
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-07-05
Hands On System Programming With Go written by Alex Guerrieri 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 2019-07-05 with Computers categories.
Explore the fundamentals of systems programming starting from kernel API and filesystem to network programming and process communications Key FeaturesLearn how to write Unix and Linux system code in Golang v1.12Perform inter-process communication using pipes, message queues, shared memory, and semaphoresExplore modern Go features such as goroutines and channels that facilitate systems programmingBook Description System software and applications were largely created using low-level languages such as C or C++. Go is a modern language that combines simplicity, concurrency, and performance, making it a good alternative for building system applications for Linux and macOS. This Go book introduces Unix and systems programming to help you understand the components the OS has to offer, ranging from the kernel API to the filesystem, and familiarize yourself with Go and its specifications. You'll also learn how to optimize input and output operations with files and streams of data, which are useful tools in building pseudo terminal applications. You'll gain insights into how processes communicate with each other, and learn about processes and daemon control using signals, pipes, and exit codes. This book will also enable you to understand how to use network communication using various protocols, including TCP and HTTP. As you advance, you'll focus on Go's best feature-concurrency helping you handle communication with channels and goroutines, other concurrency tools to synchronize shared resources, and the context package to write elegant applications. By the end of this book, you will have learned how to build concurrent system applications using Go What you will learnExplore concepts of system programming using Go and concurrencyGain insights into Golang's internals, memory models and allocationFamiliarize yourself with the filesystem and IO streams in generalHandle and control processes and daemons' lifetime via signals and pipesCommunicate with other applications effectively using a networkUse various encoding formats to serialize complex data structuresBecome well-versed in concurrency with channels, goroutines, and syncUse concurrency patterns to build robust and performant system applicationsWho this book is for If you are a developer who wants to learn system programming with Go, this book is for you. Although no knowledge of Unix and Linux system programming is necessary, intermediate knowledge of Go will help you understand the concepts covered in the book
Keras Reinforcement Learning Projects
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Author : Giuseppe Ciaburro
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-09-29
Keras Reinforcement Learning Projects written by Giuseppe Ciaburro 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 2018-09-29 with Computers categories.
A practical guide to mastering reinforcement learning algorithms using Keras Key FeaturesBuild projects across robotics, gaming, and finance fields, putting reinforcement learning (RL) into actionGet to grips with Keras and practice on real-world unstructured datasetsUncover advanced deep learning algorithms such as Monte Carlo, Markov Decision, and Q-learningBook Description Reinforcement learning has evolved a lot in the last couple of years and proven to be a successful technique in building smart and intelligent AI networks. Keras Reinforcement Learning Projects installs human-level performance into your applications using algorithms and techniques of reinforcement learning, coupled with Keras, a faster experimental library. The book begins with getting you up and running with the concepts of reinforcement learning using Keras. You’ll learn how to simulate a random walk using Markov chains and select the best portfolio using dynamic programming (DP) and Python. You’ll also explore projects such as forecasting stock prices using Monte Carlo methods, delivering vehicle routing application using Temporal Distance (TD) learning algorithms, and balancing a Rotating Mechanical System using Markov decision processes. Once you’ve understood the basics, you’ll move on to Modeling of a Segway, running a robot control system using deep reinforcement learning, and building a handwritten digit recognition model in Python using an image dataset. Finally, you’ll excel in playing the board game Go with the help of Q-Learning and reinforcement learning algorithms. By the end of this book, you’ll not only have developed hands-on training on concepts, algorithms, and techniques of reinforcement learning but also be all set to explore the world of AI. What you will learnPractice the Markov decision process in prediction and betting evaluationsImplement Monte Carlo methods to forecast environment behaviorsExplore TD learning algorithms to manage warehouse operationsConstruct a Deep Q-Network using Python and Keras to control robot movementsApply reinforcement concepts to build a handwritten digit recognition model using an image datasetAddress a game theory problem using Q-Learning and OpenAI GymWho this book is for Keras Reinforcement Learning Projects is for you if you are data scientist, machine learning developer, or AI engineer who wants to understand the fundamentals of reinforcement learning by developing practical projects. Sound knowledge of machine learning and basic familiarity with Keras is useful to get the most out of this book
Handbook Of Research On Innovation And Development Of E Commerce And E Business In Asean
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Author : Almunawar, Mohammad Nabil
language : en
Publisher: IGI Global
Release Date : 2020-08-28
Handbook Of Research On Innovation And Development Of E Commerce And E Business In Asean written by Almunawar, Mohammad Nabil and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-28 with Business & Economics categories.
Business-to-consumer (B2C) and consumer-to-consumer (C2C) e-commerce transactions, including social commerce, are rapidly expanding, although e-commerce is still small when compared to traditional business transactions. As the familiarity of making purchases using smart devices continues to expand, many global and regional investors hope to target the ASEAN region to tap into the rising digital market in this region. The Handbook of Research on Innovation and Development of E-Commerce and E-Business in ASEAN is an essential reference source that discusses economics, marketing strategies, and mobile payment systems, as well as digital marketplaces, communication technologies, and social technologies utilized for business purposes. Featuring research on topics such as business culture, mobile technology, and consumer satisfaction, this book is ideally designed for policymakers, financial managers, business professionals, academicians, students, and researchers.
Intelligent Projects Using Python
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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
Hands On Deep Learning With Go
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Author : Gareth Seneque
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-08-08
Hands On Deep Learning With Go written by Gareth Seneque 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 2019-08-08 with Computers categories.
Apply modern deep learning techniques to build and train deep neural networks using Gorgonia Key FeaturesGain a practical understanding of deep learning using GolangBuild complex neural network models using Go libraries and GorgoniaTake your deep learning model from design to deployment with this handy guideBook Description Go is an open source programming language designed by Google for handling large-scale projects efficiently. The Go ecosystem comprises some really powerful deep learning tools such as DQN and CUDA. With this book, you'll be able to use these tools to train and deploy scalable deep learning models from scratch. This deep learning book begins by introducing you to a variety of tools and libraries available in Go. It then takes you through building neural networks, including activation functions and the learning algorithms that make neural networks tick. In addition to this, you'll learn how to build advanced architectures such as autoencoders, restricted Boltzmann machines (RBMs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), and more. You'll also understand how you can scale model deployments on the AWS cloud infrastructure for training and inference. By the end of this book, you'll have mastered the art of building, training, and deploying deep learning models in Go to solve real-world problems. What you will learnExplore the Go ecosystem of libraries and communities for deep learningGet to grips with Neural Networks, their history, and how they workDesign and implement Deep Neural Networks in GoGet a strong foundation of concepts such as Backpropagation and MomentumBuild Variational Autoencoders and Restricted Boltzmann Machines using GoBuild models with CUDA and benchmark CPU and GPU modelsWho this book is for This book is for data scientists, machine learning engineers, and AI developers who want to build state-of-the-art deep learning models using Go. Familiarity with basic machine learning concepts and Go programming is required to get the best out of this book.
Collins International Lower Secondary Computing International Lower Secondary Computing Teacher S Guide Stage 7
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Author : Dr Tracy Gardner
language : en
Publisher: HarperCollins UK
Release Date : 2024-11-29
Collins International Lower Secondary Computing International Lower Secondary Computing Teacher S Guide Stage 7 written by Dr Tracy Gardner and has been published by HarperCollins UK this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-29 with Juvenile Nonfiction categories.
Collins International Lower Secondary Computing series provides in-depth coverage of the Cambridge curriculum frameworks Lower Secondary Computing (0860) and Lower Secondary Digital Literacy (0082), as well as the UK national curriculum for Computing at secondary level. The course is organised around six themes relating to computing and digital literacy – Our digital world; Content creation; Create with code; How computers work; Connect the world; The power of data. The chapter overviews and lesson summaries show how these themes are developed in Stage 7, helping teachers to plan their course. The Teacher’s Guide offers a detailed lesson plan for every unit, giving guidance on how to run the session, including lesson objectives, reference to key pedagogies, mapping grids, worksheets, resource sheets, answers, support for assessing end-of-chapter projects and ‘Build on this’ extension activities. The lesson plans and introduction provide valuable subject knowledge and support for non-specialists. This includes summaries of the key computing pedagogies used in the resources, and references to further reading to develop teachers’ own practice. Built around an internationally sound pedagogy, this framework for teaching provides real-life contexts and culturally responsive examples into a project-based approach and incorporates all learners’ knowledge, ways of learning, and heritage; where learners are given more of an opportunity to choose appropriate contexts for themselves. The accompanying downloads, available on the Collins site, includes PDF and editable Word versions of all the resources in the Teacher’s Guide, to print and adapt, as well as source files, mapping grids, worksheets, resource sheets and recommended sites to support practical tasks with a host of resources to supplement teaching. Written by Flip Computing, a team of female experts who have a breadth of computing experience across industry, education and research, and their culturally responsive approach provides teachers with an accessible and inclusive learning experience for all ages and inspires greater participation and tech career pathways for all. Supports teachers to prepare learners for a seamless transition to Lower Secondary Computing Stage 8.
Machine Learning And Deep Learning Using Python And Tensorflow
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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
Collins International Lower Secondary Computing International Lower Secondary Computing Student S Book Stage 7
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Author : Dr Tracy Gardner
language : en
Publisher: HarperCollins UK
Release Date : 2024-11-29
Collins International Lower Secondary Computing International Lower Secondary Computing Student S Book Stage 7 written by Dr Tracy Gardner and has been published by HarperCollins UK this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-29 with Juvenile Nonfiction categories.
Collins International Lower Secondary Computing series is structured around six themes relating to computing and digital literacy and offers learners a comprehensive and engaging approach to learning, enhanced by real-world applications. Each chapter is organised to develop essential skills, leading learners towards the creation of a final project.
Knowledge Acquisition In Civil Engineering
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Author : Tomasz Arciszewski
language : en
Publisher:
Release Date : 1992
Knowledge Acquisition In Civil Engineering written by Tomasz Arciszewski and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Computers categories.
A comprehensive view of knowledge acquisition in civil engineering, reflecting both recent theoretical developments in computer science as well as the practical experience gained by civil engineers building expert systems in the past few years. Includes a ten-page annotated bibliography. Annotation copyright Book News, Inc. Portland, Or.