Machine Learning With Go Quick Start Guide
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Machine Learning With Go Quick Start Guide
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Author : Michael Bironneau
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-05-31
Machine Learning With Go Quick Start Guide written by Michael Bironneau 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 2019-05-31 with Computers categories.
This quick start guide will bring the readers to a basic level of understanding when it comes to the Machine Learning (ML) development lifecycle, will introduce Go ML libraries and then will exemplify common ML methods such as Classification, Regression, and Clustering Key FeaturesYour handy guide to building machine learning workflows in Go for real-world scenariosBuild predictive models using the popular supervised and unsupervised machine learning techniquesLearn all about deployment strategies and take your ML application from prototype to production readyBook Description Machine learning is an essential part of today's data-driven world and is extensively used across industries, including financial forecasting, robotics, and web technology. This book will teach you how to efficiently develop machine learning applications in Go. The book starts with an introduction to machine learning and its development process, explaining the types of problems that it aims to solve and the solutions it offers. It then covers setting up a frictionless Go development environment, including running Go interactively with Jupyter notebooks. Finally, common data processing techniques are introduced. The book then teaches the reader about supervised and unsupervised learning techniques through worked examples that include the implementation of evaluation metrics. These worked examples make use of the prominent open-source libraries GoML and Gonum. The book also teaches readers how to load a pre-trained model and use it to make predictions. It then moves on to the operational side of running machine learning applications: deployment, Continuous Integration, and helpful advice for effective logging and monitoring. At the end of the book, readers will learn how to set up a machine learning project for success, formulating realistic success criteria and accurately translating business requirements into technical ones. What you will learnUnderstand the types of problem that machine learning solves, and the various approachesImport, pre-process, and explore data with Go to make it ready for machine learning algorithmsVisualize data with gonum/plot and GophernotesDiagnose common machine learning problems, such as overfitting and underfittingImplement supervised and unsupervised learning algorithms using Go librariesBuild a simple web service around a model and use it to make predictionsWho this book is for This book is for developers and data scientists with at least beginner-level knowledge of Go, and a vague idea of what types of problem Machine Learning aims to tackle. No advanced knowledge of Go (and no theoretical understanding of the math that underpins Machine Learning) is required.
Deep Learning With Pytorch Quick Start Guide
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Author : David Julian
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-12-24
Deep Learning With Pytorch Quick Start Guide written by David Julian 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 2018-12-24 with Computers categories.
Introduction to deep learning and PyTorch by building a convolutional neural network and recurrent neural network for real-world use cases such as image classification, transfer learning, and natural language processing. Key FeaturesClear and concise explanationsGives important insights into deep learning modelsPractical demonstration of key conceptsBook Description PyTorch is extremely powerful and yet easy to learn. It provides advanced features, such as supporting multiprocessor, distributed, and parallel computation. This book is an excellent entry point for those wanting to explore deep learning with PyTorch to harness its power. This book will introduce you to the PyTorch deep learning library and teach you how to train deep learning models without any hassle. We will set up the deep learning environment using PyTorch, and then train and deploy different types of deep learning models, such as CNN, RNN, and autoencoders. You will learn how to optimize models by tuning hyperparameters and how to use PyTorch in multiprocessor and distributed environments. We will discuss long short-term memory network (LSTMs) and build a language model to predict text. By the end of this book, you will be familiar with PyTorch's capabilities and be able to utilize the library to train your neural networks with relative ease. What you will learnSet up the deep learning environment using the PyTorch libraryLearn to build a deep learning model for image classificationUse a convolutional neural network for transfer learningUnderstand to use PyTorch for natural language processingUse a recurrent neural network to classify textUnderstand how to optimize PyTorch in multiprocessor and distributed environmentsTrain, optimize, and deploy your neural networks for maximum accuracy and performanceLearn to deploy production-ready modelsWho this book is for Developers and Data Scientist familiar with Machine Learning but new to deep learning, or existing practitioners of deep learning who would like to use PyTorch to train their deep learning models will find this book to be useful. Having knowledge of Python programming will be an added advantage, while previous exposure to PyTorch is not needed.
Machine Learning
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Author : Dr. Mohammad Anwarul Siddique, Dr. D. Venkata Siva Reddy, Dr. Ajith V S, Dr. Jyoti Singh
language : en
Publisher: BR Publications
Release Date : 2025-08-28
Machine Learning written by Dr. Mohammad Anwarul Siddique, Dr. D. Venkata Siva Reddy, Dr. Ajith V S, Dr. Jyoti Singh and has been published by BR Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-28 with Computers categories.
Machine Learning is a branch of Artificial Intelligence (AI) that enables computers to learn patterns and make decisions from data without being explicitly programmed. It involves developing algorithms and statistical models that allow systems to automatically improve their performance through experience. ML techniques are widely used in diverse domains such as image and speech recognition, predictive analytics, healthcare, finance, and robotics. The major categories of ML include supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning.
Python For Machine Learning
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Author : Jason Brownlee
language : en
Publisher: Machine Learning Mastery
Release Date : 2022-05-25
Python For Machine Learning written by Jason Brownlee and has been published by Machine Learning Mastery this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-25 with Computers categories.
Using clear explanations and step-by-step tutorial lessons, you will learn the underlying mechanics of the Python language, the tools in its ecosystem, tips and tricks, and much more.
The Aviation Fire Officer Reference
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Author : Eric J. Russell
language : en
Publisher: Fire Engineering Books
Release Date :
The Aviation Fire Officer Reference written by Eric J. Russell and has been published by Fire Engineering Books this book supported file pdf, txt, epub, kindle and other format this book has been release on with Technology & Engineering categories.
The Aviation Fire Officer Reference by Eric J.. Russell equips current and aspiring ARFF officers with leadership strategies, hazard response tactics, and guidance aligned with FAA, NFPA, ICAO, and DoD standards.
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.
Infoworld
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Author :
language : en
Publisher:
Release Date : 1989
Infoworld written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989 with Computer industry categories.
R Machine Learning By Example
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Author : Raghav Bali
language : en
Publisher:
Release Date : 2016
R Machine Learning By Example written by Raghav Bali and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Computers categories.
Understand the fundamentals of machine learning with R and build your own dynamic algorithms to tackle complicated real-world problems successfullyAbout This Book* Get to grips with the concepts of machine learning through exciting real-world examples* Visualize and solve complex problems by using power-packed R constructs and its robust packages for machine learning* Learn to build your own machine learning system with this example-based practical guideWho This Book Is ForIf you are interested in mining useful information from data using state-of-the-art techniques to make data-driven decisions, this is a go-to guide for you. No prior experience with data science is required, although basic knowledge of R is highly desirable. Prior knowledge in machine learning would be helpful but is not necessary.What You Will Learn* Utilize the power of R to handle data extraction, manipulation, and exploration techniques* Use R to visualize data spread across multiple dimensions and extract useful features* Explore the underlying mathematical and logical concepts that drive machine learning algorithms* Dive deep into the world of analytics to predict situations correctly* Implement R machine learning algorithms from scratch and be amazed to see the algorithms in action* Write reusable code and build complete machine learning systems from the ground up* Solve interesting real-world problems using machine learning and R as the journey unfolds* Harness the power of robust and optimized R packages to work on projects that solve real-world problems in machine learning and data scienceIn DetailData science and machine learning are some of the top buzzwords in the technical world today. From retail stores to Fortune 500 companies, everyone is working hard to making machine learning give them data-driven insights to grow their business. With powerful data manipulation features, machine learning packages, and an active developer community, R empowers users to build sophisticated machine learning systems to solve real-world data problems.This book takes you on a data-driven journey that starts with the very basics of R and machine learning and gradually builds upon the concepts to work on projects that tackle real-world problems.You'll begin by getting an understanding of the core concepts and definitions required to appreciate machine learning algorithms and concepts. Building upon the basics, you will then work on three different projects to apply the concepts of machine learning, following current trends and cover major algorithms as well as popular R packages in detail. These projects have been neatly divided into six different chapters covering the worlds of e-commerce, finance, and social-media, which are at the very core of this data-driven revolution. Each of the projects will help you to understand, explore, visualize, and derive insights depending upon the domain and algorithms.Through this book, you will learn to apply the concepts of machine learning to deal with data-related problems and solve them using the powerful yet simple language, R.Style and approachThe book is an enticing journey that starts from the very basics to gradually pick up pace as the story unfolds. Each concept is first defined in the larger context of things succinctly, followed by a detailed explanation of their application. Each topic is explained with the help of a project that solves a real real-world problem involving hands-on work thus giving you a deep insight into the world of machine learning.
Microsoft Excel 2000 Bible
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Author : John Walkenbach
language : en
Publisher: Wiley
Release Date : 1999
Microsoft Excel 2000 Bible written by John Walkenbach and has been published by Wiley this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Computers categories.
You, too, can excel -- especially with expert advice from one of the country's leading authorities on spreadsheet software. Whenever you get stuck or need to learn something you've never done before, turn to Microsoft Excel 2000 Bible. With plenty of examples and little-known tips, John Walkenbach guides you step-by-step through the entire program -- from basic cell formatting to the exciting new Web capabilities of Excel 2000.
Microsoft Word 2000 Bible
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Author : Brent Heslop and David Angell
language : en
Publisher:
Release Date : 1999
Microsoft Word 2000 Bible written by Brent Heslop and David Angell and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with categories.