Hands-On Machine Learning with C++: Build, train, and deploy end-to-end machine learning and deep learning pipelines
genuine image
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
Artikelnr.: 32273991

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

Artikelnr.: 32273991

€ 56

Price Details

Excluding Shipping & Custom charges ( Shipping and custom charges will be calculated on checkout )

*All items will import from USA

Auf Lager
USA Vom USA Store für Sie importiert

QTY:

Bestellen Sie jetzt und erhalten Sie es am Donnerstag, Juni 25
Gesicherte TransaktionGesicherte Transaktion

Ubuy ist bestrebt, Ihre Sicherheit und Privatsphäre zu schützen. Unser fortschrittliches Zahlungssicherheitssystem gewährleistet Vertraulichkeit, indem Ihre Daten während der Übertragung mit AES (Advanced Encryption Standards) und SSL (Secure Socket Layer) Protokollen verschlüsselt werden. Ihre Zahlungsdaten sind 100% sicher, da wir Ihre Zahlungsdaten nicht an Drittanbieter weitergeben.

Unsere besten Logistigpartner
  • fedex
  • dhl
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.
U-Care-Garantie:
Keine
Wählen Sie einen Plan aus
fast shipping

Fast
Shipping

free return

Kostenlose
Rücksendung*

Sichere Verpackung

Sichere Verpackung

100 % Originalprodukte

100 % Originalprodukte

pci-dss

PCI DSS-Standards

iso certified

ISO 27001-zertifiziert

paypal payment
visa payment
mastercard payment
american express payment
eps payment
Note: Step Down Voltage Transformer required for using electronics products of USA store (110-120). Recommended power converters Jetzt kaufen.

Besondere Merkmale

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.

Produktdetails

Discover the power of machine learning and deep learning with C. Build, train, and deploy end-to-end ML pipelines. Shop now at Ubuy Austria.
Item Weight1.5 lbs (680 grams)

Für wen ist das Produkt geeignet?

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.

  • Python Users

    Developers accustomed to Python may find C++ implementations unfamiliar and thus may not find the content applicable.

  • Casual Learners

    Those seeking a light introduction to machine learning without deep coding might find this book overly complex.

PRODUKTBESCHREIBUNG

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

Haben Sie eine Frage? Mit uns chatten

Kunden Fragen und Antworten

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

    Antworten: 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.
  • Frage: Who is the target audience for this book?

    Antworten: 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.
  • Frage: What types of projects can I expect to find in this book?

    Antworten: 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.
  • Frage: Does this book cover deep learning as well?

    Antworten: 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.
  • Frage: Is prior knowledge of machine learning required?

    Antworten: 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.
  • Frage: Can I apply the techniques learned in this book to real-world scenarios?

    Antworten: 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.
  • Frage: What programming aspects are covered in the book?

    Antworten: 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.
  • Frage: How does the book facilitate learning for beginners?

    Antworten: 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.
  • Frage: Are there any online resources or communities associated with this book?

    Antworten: 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.
  • Frage: Where can I buy 'Hands-On Machine Learning with C' in Austria?

    Antworten: 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.

Kundenbewertungen

5.0
1 Kundenbewertungen
  • 5 Sterne
    100%
  • 4 Sterne
    0%
  • 3 Sterne
    0%
  • 2 Sterne
    0%
  • 1 Sterne
    0%

Bewerten Sie dieses Produkt

Teilen Sie Ihre Meinung mit anderen Kunden

Vorteile

  • 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

Nachteile

  • Requires a Visual Studio 2019 configuration for the examples

Produktpreisverlauf

Wichtige Information

  • Einschränkungen: Für international versandte Produkte beachten Sie bitte, dass jegliche Herstellergarantie nicht gültig sein könnte; Herstellerservice-Optionen nicht verfügbar sein könnten; Produkthandbücher, Gebrauchsanleitungen und Sicherheitshinweise nicht in der Sprache des Ziellandes verfasst sein könnten; die Produkte (und Begleitmaterialien) könnten nicht im Einklang mit den Standards, Spezifizierungen und Etikettierungsvorgaben des Ziellandes entworfen sein; und die Produkte könnten nicht der Voltzahl und anderen elektrischen Standards des Ziellandes entsprechen (weshalb, falls zutreffend, die Verwendung eines Adapters oder Umwandlers erforderlich sein könnte). Der Empfänger ist dafür verantwortlich sicherzustellen, dass das Produkt legal in das Zielland importiert werden kann. Bei der Bestellung von Ubuy oder seinen Partnern ist der Empfänger der eingetragene Importeur und muss sich an alle Gesetze und Regulierungen des Ziellandes halten.
  • Nicht alle auf Ubuy aufgeführten Produkte werden zum Verkauf angeboten, da Ubuy eine globale Suchmaschine ist. Produkte unterliegen Export-/Handelsbestimmungen.

€ 56

Bestellen Sie jetzt und erhalten Sie es am Donnerstag, Juni 25

QTY:

Gesicherte TransaktionGesicherte Transaktion

Ubuy ist bestrebt, Ihre Sicherheit und Privatsphäre zu schützen. Unser fortschrittliches Zahlungssicherheitssystem gewährleistet Vertraulichkeit, indem Ihre Daten während der Übertragung mit AES (Advanced Encryption Standards) und SSL (Secure Socket Layer) Protokollen verschlüsselt werden. Ihre Zahlungsdaten sind 100% sicher, da wir Ihre Zahlungsdaten nicht an Drittanbieter weitergeben.

Unsere besten Logistigpartner
  • fedex
  • dhl
Schnellste grenzüberschreitende Lieferung

Merkmale und Vorteile

  • 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++.