Hands-On Machine Learning with C++: Build, train, and deploy end-to-end machine learning and deep learning pipelines
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Hands-On Machine Learning with C++: Build, train, and deploy end-to-end machine learning and deep learning pipelines
This handy guide will help you learn the fundamentals of machine learning (ML), showing you how to use C++ libraries to get the most out of your data.
Hands-On Machine Learning with C++: Build, train, and deploy end-to-end machine learning and deep learning pipelines
Articol nr.: 32273991

Hands-On Machine Learning with C++: Build, train, and deploy end-to-end machine learning and deep learning pipelines

Articol nr.: 32273991

MDL 1200

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This handy guide will help you learn the fundamentals of machine learning (ML), showing you how to use C++ libraries to get the most out of your data.
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Ce Iese în evidență

End-to-End Pipeline
Offers comprehensive guidance on building, training, and deploying machine learning models, ensuring users can implement complete solutions from start to finish.
C++ Focus
Utilizes C++ for performance-driven applications, making it ideal for software engineers looking to integrate machine learning into high-performance systems.
Practical Learning
Emphasizes hands-on projects to enhance understanding, allowing readers to apply concepts in real-world scenarios effectively.

Detalii produs

Discover the power of machine learning and deep learning with C. Build, train, and deploy end-to-end ML pipelines. Shop now at Ubuy Moldova.
Publisher Packt Publishing
Publication date May 15, 2020
Language English
Print length 530 pages
ISBN-10 1789955335
ISBN-13 978-1789955330
Item Weight 2.21 pounds (1 kg)
Dimensions 7.5 x 1.2 x 9.25 inches (19.1 x 3 x 23.5 cm)

Cine Ar Trebui să Cumpere?

Suitable For
  • Beginner Developers

    New developers can learn machine learning concepts effectively through practical examples and hands-on projects with C++.

  • Data Scientists

    Data scientists looking to implement machine learning models in production will benefit from end-to-end project coverage.

  • C++ Enthusiasts

    C++ programmers eager to apply their skills to machine learning will find this book particularly useful and engaging.

Not Suitable For
  • Non-Technical Users

    Users without a programming background may struggle with the technical content and programming requirements of the book.

DESCRIEREA PRODUSULUI

Hands-On Machine Learning with C++: Build, train, and deploy end-to-end machine learning and deep learning pipelines

Aveți întrebări? Discutați cu noi

Întrebări și răspunsuri ale clienților

  • Întrebare: What is 'Hands-On Machine Learning with C' about?

    Răspuns: This book offers a comprehensive introduction to building, training, and deploying machine learning and deep learning models using C. It guides readers through practical applications and hands-on projects, which include creating data pipelines, preprocessing data, and implementing algorithms. The structured approach makes it ideal for both beginners and seasoned developers looking to enhance their understanding of machine learning concepts through practical coding examples.
  • Întrebare: Who is the target audience for this book?

    Răspuns: The primary audience for 'Hands-On Machine Learning with C' includes software developers, data scientists, and students interested in machine learning. It’s perfect for those with a background in programming seeking to delve into ML concepts. The book assumes a fundamental understanding of C programming and queuing theory, catering to readers who are looking to engage in project-based learning while strengthening their skills in machine learning applications.
  • Întrebare: What types of projects can I expect to find in this book?

    Răspuns: The book contains a variety of practical projects, including building a simple machine learning model, implementing neural networks from scratch, and deploying models. These projects illustrate key concepts while enabling readers to apply what they learn in a hands-on manner. For example, you may work on tasks such as image classification or predictive analytics, which are highly relevant in real-world applications across different industries.
  • Întrebare: Does this book cover deep learning as well?

    Răspuns: Yes, 'Hands-On Machine Learning with C' thoroughly covers both machine learning and deep learning. It dives into essential topics such as neural networks, convolutional neural networks, and sequential models. By integrating deep learning with practical examples, readers can better grasp how to leverage these advanced techniques for more complex datasets and applications, enhancing their ability to work on cutting-edge projects in machine learning.
  • Întrebare: Is prior knowledge of machine learning required?

    Răspuns: While prior knowledge of machine learning isn’t strictly necessary, some familiarity with basic concepts can be beneficial. The book starts with fundamental principles but quickly progresses to more complex topics. If you're new to the field, you might find it useful to complement your learning with introductory resources. Engaging with this book will strengthen your coding skills while building your foundational understanding of machine learning methods.
  • Întrebare: Can I apply the techniques learned in this book to real-world scenarios?

    Răspuns: Absolutely! The techniques detailed in 'Hands-On Machine Learning with C' are designed for real-world applications. Each project not only helps you understand the theoretical aspects but also prepares you for industry practices. You can apply your skills in various fields, such as finance for algorithmic trading, healthcare for predictive analytics, or even in developing smart applications that rely on machine learning capabilities.
  • Întrebare: What programming aspects are covered in the book?

    Răspuns: The book covers several programming aspects relevant to machine learning with C, including data handling, model training, and performance optimization techniques. It teaches you how to manipulate data using C libraries and implement machine learning algorithms from scratch, giving you a robust understanding of the underlying mechanics. These skills are invaluable for any programmer looking to enhance their ability to work with data-intensive applications.
  • Întrebare: How does the book facilitate learning for beginners?

    Răspuns: The book is structured to facilitate learning through a project-oriented approach, making it accessible for beginners. Each chapter builds on the previous one, gradually introducing more complex topics and ensuring comprehension. Additionally, the authors include clear explanations of concepts and coding practices, enabling beginners to follow along with confidence and apply what they learn directly to their projects.
  • Întrebare: Are there any online resources or communities associated with this book?

    Răspuns: Yes, many readers often share insights and discuss problems related to the book in various online communities, such as GitHub and forums dedicated to machine learning. These platforms allow readers to collaborate, share their projects, and seek help on challenging sections. Engaging in these communities can significantly enhance your learning experience as you exchange ideas and solutions with peers who share your interest in machine learning.
  • Întrebare: Where can I buy 'Hands-On Machine Learning with C' in Moldova?

    Răspuns: You can purchase 'Hands-On Machine Learning with C' from Ubuy, a reliable online retail platform that caters to various products including educational materials like this book. Ubuy often offers a straightforward shopping experience, ensuring you have access to this essential resource for enhancing your machine learning skills.

Natural Language Processing Editorial Review

Hands-On Machine Learning with C++ is a valuable resource for C++ programmers looking to enter the world of machine learning and deep learning. The book fills a significant gap in educational resources for C++ developers interested in these fields. The author provides clear explanations of the mathematical theory, along with complete examples that allow readers to immediately apply their knowledge to real-life projects. The book strikes a good balance between theory and implementation, making it accessible to developers new to data science. One of the standout features is the inclusion of a PyTorch Deep Learning library for C++ code use, enabling high-performance GPU programming with a tensor interface. Overall, this book is a time-saving tool that expands the programming scope of C++ developers without the need to transition to Python.

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Pro

  • Clear explanations of mathematical theory
  • Complete examples with real-life datasets
  • Accessible for developers new to data science
  • Includes a PyTorch Deep Learning library for C++ code use
  • Saves time and expands the programming scope of C++ developers

Contra

  • Requires a Visual Studio 2019 configuration for the examples

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MDL 1200

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Caracteristici și avantaje

  • Learn the fundamentals of machine learning using C++ libraries.
  • Implement supervised and unsupervised ML algorithms through real-world examples.
  • Tune and optimize models for different use cases, measure performance.
  • Handle production and deployment challenges on mobile and cloud platforms.
  • Use C++ to build powerful ML systems.
  • Suitable for beginners and professionals with working knowledge of C++.

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