Machine Learning Projects For Net Developers
DOWNLOAD
Download Machine Learning Projects For Net Developers PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Machine Learning Projects For Net Developers 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
Machine Learning Projects For Net Developers
DOWNLOAD
Author : Mathias Brandewinder
language : en
Publisher: Apress
Release Date : 2015-07-09
Machine Learning Projects For Net Developers written by Mathias Brandewinder and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-09 with Computers categories.
Machine Learning Projects for .NET Developers shows you how to build smarter .NET applications that learn from data, using simple algorithms and techniques that can be applied to a wide range of real-world problems. You’ll code each project in the familiar setting of Visual Studio, while the machine learning logic uses F#, a language ideally suited to machine learning applications in .NET. If you’re new to F#, this book will give you everything you need to get started. If you’re already familiar with F#, this is your chance to put the language into action in an exciting new context. In a series of fascinating projects, you’ll learn how to: Build an optical character recognition (OCR) system from scratch Code a spam filter that learns by example Use F#’s powerful type providers to interface with external resources (in this case, data analysis tools from the R programming language) Transform your data into informative features, and use them to make accurate predictions Find patterns in data when you don’t know what you’re looking for Predict numerical values using regression models Implement an intelligent game that learns how to play from experience Along the way, you’ll learn fundamental ideas that can be applied in all kinds of real-world contexts and industries, from advertising to finance, medicine, and scientific research. While some machine learning algorithms use fairly advanced mathematics, this book focuses on simple but effective approaches. If you enjoy hacking code and data, this book is for you.
Machine Learning Projects For Net Developers
DOWNLOAD
Author : Mathias Brandewinder
language : en
Publisher: Apress
Release Date : 2015-07-14
Machine Learning Projects For Net Developers written by Mathias Brandewinder and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-14 with Computers categories.
Machine Learning Projects for .NET Developers shows you how to build smarter .NET applications that learn from data, using simple algorithms and techniques that can be applied to a wide range of real-world problems. You’ll code each project in the familiar setting of Visual Studio, while the machine learning logic uses F#, a language ideally suited to machine learning applications in .NET. If you’re new to F#, this book will give you everything you need to get started. If you’re already familiar with F#, this is your chance to put the language into action in an exciting new context. In a series of fascinating projects, you’ll learn how to: Build an optical character recognition (OCR) system from scratch Code a spam filter that learns by example Use F#’s powerful type providers to interface with external resources (in this case, data analysis tools from the R programming language) Transform your data into informative features, and use them to make accurate predictions Find patterns in data when you don’t know what you’re looking for Predict numerical values using regression models Implement an intelligent game that learns how to play from experience Along the way, you’ll learn fundamental ideas that can be applied in all kinds of real-world contexts and industries, from advertising to finance, medicine, and scientific research. While some machine learning algorithms use fairly advanced mathematics, this book focuses on simple but effective approaches. If you enjoy hacking code and data, this book is for you.
Deep Learning For Coders With Fastai And Pytorch
DOWNLOAD
Author : Jeremy Howard
language : en
Publisher: O'Reilly Media
Release Date : 2020-06-29
Deep Learning For Coders With Fastai And Pytorch written by Jeremy Howard 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 2020-06-29 with Computers categories.
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
Deep Learning With C Net And Kelp Net
DOWNLOAD
Author : Matt R. Cole
language : en
Publisher: BPB Publications
Release Date : 2019-05-14
Deep Learning With C Net And Kelp Net written by Matt R. Cole and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-14 with Computers categories.
Get hands on with Kelp.Net , MicrosoftÕs latest Deep Learning framework Description Deep Learning with Kelp.Net is the ultimate reference for C# .Net developers who are passionate about deep learning. Readers will learn all the skills necessary to develop powerful, scalable and flexible deep learning models from a fluid and easy to use API. Upon completing the book the reader will have all the tools necessary to add powerful deep learning capabilities to their new or existing applications. Key Features Deep Learning Basics The ultimate Kelp.Net reference guide Develop state of the art deep learning applications C# Deep Learning code Develop advanced deep learning models with minimal code Develop your own advanced Deep Learning models Loading and Saving Deep Learning Models Comprehensive Kelp.Net reference Sample Deep Learning Models and Tests OpenCL Reference Easily add deep learning to your applications Many sample models and tests Intuitive and user friendly What you will learn In-depth knowledge of Kelp.Net How to develop Deep Learning models C# Deep Learning programming Open-Computing Language (OpenCL) Loading and saving Deep Learning models How to develop and use activation functions How to test Deep Learning models Who This Book is For This book targets C# .Net developers who are passionate about deep learning yet want to do so from an easy and intuitive API. Table of Contents Introduction ML/DL Terms and Concepts Deep Instrumentation Kelp.Net Reference Loading and Saving Models Model Testing and Training Sample Deep Learning Tests Creating Your Own Deep Learning Tests Appendix A: Evaluation Metrics Appendix B: OpenCL
Machine Learning For Decision Makers
DOWNLOAD
Author : Patanjali Kashyap
language : en
Publisher: Apress
Release Date : 2018-01-04
Machine Learning For Decision Makers written by Patanjali Kashyap and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-04 with Computers categories.
Take a deep dive into the concepts of machine learning as they apply to contemporary business and management. You will learn how machine learning techniques are used to solve fundamental and complex problems in society and industry. Machine Learning for Decision Makers serves as an excellent resource for establishing the relationship of machine learning with IoT, big data, and cognitive and cloud computing to give you an overview of how these modern areas of computing relate to each other. This book introduces a collection of the most important concepts of machine learning and sets them in context with other vital technologies that decision makers need to know about. These concepts span the process from envisioning the problem to applying machine-learning techniques to your particular situation. This discussion also provides an insight to help deploy the results to improve decision-making. The book usescase studies and jargon busting to help you grasp the theory of machine learning quickly. You'll soon gain the big picture of machine learning and how it fits with other cutting-edge IT services. This knowledge will give you confidence in your decisions for the future of your business. What You Will Learn Discover the machine learning, big data, and cloud and cognitive computing technology stack Gain insights into machine learning concepts and practices Understand business and enterprise decision-making using machine learning Absorb machine-learning best practices Who This Book Is For Managers tasked with making key decisions who want to learn how and when machine learning and related technologies can help them.
Deep Learning Projects Using Tensorflow 2
DOWNLOAD
Author : Vinita Silaparasetty
language : en
Publisher: Apress
Release Date : 2020-08-08
Deep Learning Projects Using Tensorflow 2 written by Vinita Silaparasetty and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-08 with Computers categories.
Work through engaging and practical deep learning projects using TensorFlow 2.0. Using a hands-on approach, the projects in this book will lead new programmers through the basics into developing practical deep learning applications. Deep learning is quickly integrating itself into the technology landscape. Its applications range from applicable data science to deep fakes and so much more. It is crucial for aspiring data scientists or those who want to enter the field of AI to understand deep learning concepts. The best way to learn is by doing. You'll develop a working knowledge of not only TensorFlow, but also related technologies such as Python and Keras. You'll also work with Neural Networks and other deep learning concepts. By the end of the book, you'll have a collection of unique projects that you can add to your GitHub profiles and expand on for professional application. What You'll Learn Grasp the basic process of neural networks through projects, such as creating music Restore and colorize black and white images with deep learning processes Who This Book Is For Beginners new to TensorFlow and Python.
Introducing Machine Learning
DOWNLOAD
Author : Dino Esposito
language : en
Publisher: Microsoft Press
Release Date : 2020-01-31
Introducing Machine Learning written by Dino Esposito and has been published by Microsoft Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-31 with Computers categories.
Master machine learning concepts and develop real-world solutions Machine learning offers immense opportunities, and Introducing Machine Learning delivers practical knowledge to make the most of them. Dino and Francesco Esposito start with a quick overview of the foundations of artificial intelligence and the basic steps of any machine learning project. Next, they introduce Microsoft’s powerful ML.NET library, including capabilities for data processing, training, and evaluation. They present families of algorithms that can be trained to solve real-life problems, as well as deep learning techniques utilizing neural networks. The authors conclude by introducing valuable runtime services available through the Azure cloud platform and consider the long-term business vision for machine learning. · 14-time Microsoft MVP Dino Esposito and Francesco Esposito help you · Explore what’s known about how humans learn and how intelligent software is built · Discover which problems machine learning can address · Understand the machine learning pipeline: the steps leading to a deliverable model · Use AutoML to automatically select the best pipeline for any problem and dataset · Master ML.NET, implement its pipeline, and apply its tasks and algorithms · Explore the mathematical foundations of machine learning · Make predictions, improve decision-making, and apply probabilistic methods · Group data via classification and clustering · Learn the fundamentals of deep learning, including neural network design · Leverage AI cloud services to build better real-world solutions faster About This Book · For professionals who want to build machine learning applications: both developers who need data science skills and data scientists who need relevant programming skills · Includes examples of machine learning coding scenarios built using the ML.NET library
Microsoft Azure Ai A Beginner S Guide
DOWNLOAD
Author : Rekha Kodali
language : en
Publisher: BPB Publications
Release Date : 2022-04-21
Microsoft Azure Ai A Beginner S Guide written by Rekha Kodali and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-21 with Computers categories.
Explore Azure AI Platform KEY FEATURES ● Easy-to-follow tutorial for getting started with the Azure AI platform. ● Integrated platform for developing, deploying, and managing AI apps. ● Includes real-world scenarios and use-cases to fully explore Azure AI Platform. DESCRIPTION Microsoft Azure AI A Beginner's Guide explains the fundamentals of Azure AI and some more advanced topics. The sole objective of the book is to provide hands-on experience working with the various services, APIs, and tools available in the Azure AI Platform. This book begins by discussing the fundamentals of the Azure AI platform and the essential principles behind the Azure AI ecosystem and services. Readers will become familiar with the essential services, use cases, and examples provided by Azure AI Platform and Services, including Azure Cognitive Services, Azure Computer Vision, Azure Applied AI Services, and Azure Machine Learning. The author focuses on teaching how to utilize Azure Cognitive services to construct intelligent apps, including Image Processing, Object Detection, Text Recognition, OCR, Spatial Analysis, and Face Recognition using Computer Vision. Readers can investigate Azure Applied AI Services, including Form Recognizer, Metrics Advisor, Cognitive Search, Immersive Reader, Video Analyzer, and Azure Bot Service. Bot Framework and the Bot Framework Emulator will be explored in further detail, and how they can be used in AI applications to improve their conversational user interfaces. With Azure Machine Learning Studio, you will also learn to incorporate machine learning into your enterprise-level applications. WHAT YOU WILL LEARN ● Get familiar with Azure AI Platform and the cognitive capabilities of Azure. ● Learn to create apps that can process photos, detect faces, and detect objects. ● Utilize OCR, handwriting recognition, and spatial analysis in your development. ● Learn about Azure AI services like Form Recognizer, Metrics Advisor, Cognitive Search, Azure Immersive Reader, and Video Analyzer. ● Try out several NLP applications with the Azure BOT framework. WHO THIS BOOK IS FOR This book teaches AI developers, machine learning engineers, .NET developers, and architects how to swiftly develop intelligent applications utilizing the Azure AI Platform. Knowledge of.NET or.NET Core is strongly advised to get the most out of the book. TABLE OF CONTENTS 1 .Azure AI Platform and Services 2. Azure Computer Vision - Image Analysis, Processing, Content Moderation, Object and Face Detection 3. Computer Vision - Text Recognition, Optical Character Recognition, Spatial Analysis 4. Azure Cognitive Services - Custom Applications leveraging Decision, Language, Speech, Web Search 5. Azure Applied AI Services 6. Azure Applied AI Services -BOTs– A Brief Introduction 7. Machine Learning-Infusing ML in Custom Applications using ML.NET 8. Machine Learning - Using Azure ML Studio
Machine Learning Projects For Net Developers
DOWNLOAD
Author : Mathias Brandewinder
language : en
Publisher: Apress
Release Date : 2014-11-27
Machine Learning Projects For Net Developers written by Mathias Brandewinder and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-27 with Computers categories.
Machine Learning Projects for .NET Developers shows you how to build smarter .NET applications that learn from data, using simple algorithms and techniques that can be applied to a wide range of real-world problems. You’ll code each project in the familiar setting of Visual Studio, while the machine learning logic uses F#, a language ideally suited to machine learning applications in .NET. If you’re new to F#, this book will give you everything you need to get started. If you’re already familiar with F#, this is your chance to put the language into action in an exciting new context. In a series of fascinating projects, you’ll learn how to: Build an optical character recognition (OCR) system from scratch Code a spam filter that learns by example Use F#’s powerful type providers to interface with external resources (in this case, data analysis tools from the R programming language) Transform your data into informative features, and use them to make accurate predictions Find patterns in data when you don’t know what you’re looking for Predict numerical values using regression models Implement an intelligent game that learns how to play from experience Along the way, you’ll learn fundamental ideas that can be applied in all kinds of real-world contexts and industries, from advertising to finance, medicine, and scientific research. While some machine learning algorithms use fairly advanced mathematics, this book focuses on simple but effective approaches. If you enjoy hacking code and data, this book is for you.
Practical Machine Learning With Rust
DOWNLOAD
Author : Joydeep Bhattacharjee
language : en
Publisher: Apress
Release Date : 2019-12-10
Practical Machine Learning With Rust written by Joydeep Bhattacharjee and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-10 with Mathematics categories.
Explore machine learning in Rust and learn about the intricacies of creating machine learning applications. This book begins by covering the important concepts of machine learning such as supervised, unsupervised, and reinforcement learning, and the basics of Rust. Further, you’ll dive into the more specific fields of machine learning, such as computer vision and natural language processing, and look at the Rust libraries that help create applications for those domains. We will also look at how to deploy these applications either on site or over the cloud. After reading Practical Machine Learning with Rust, you will have a solid understanding of creating high computation libraries using Rust. Armed with the knowledge of this amazing language, you will be able to create applications that are more performant, memory safe, and less resource heavy. What You Will Learn Write machine learning algorithms in Rust Use Rust libraries for different tasks in machine learning Create concise Rust packages for your machine learning applications Implement NLP and computer vision in Rust Deploy your code in the cloud and on bare metal servers Who This Book Is For Machine learning engineers and software engineers interested in building machine learning applications in Rust.