Ver Original
0 ratings
Machine Learning Engineering with Python: Manage the lifecycle of machine learning models using MLOps with practical examples
genuine image
Machine Learning Engineering with Python: Manage the lifecycle of machine learning models using MLOps with practical examples
Transform your machine learning projects into successful deployments with this practical guide on how to build and scale solutions that solve real-world problems
Machine Learning Engineering with Python: Manage the lifecycle of machine learning models using MLOps with practical examples
Artigo n.º: 74233457

Machine Learning Engineering with Python: Manage the lifecycle of machine learning models using MLOps with practical examples

Artigo n.º: 74233457

AOA 55457

Detalhes do Preço

Excluindo custos de envio e alfandegários ( Os custos de envio e alfandegários serão calculados na finalização da compra )

*Todos os artigos serão importados de EUA

Em stock
EUA Importado da loja USA

Qtd.:

Encomende já e receba por volta de Sexta-Feira, Agosto 28
Transação seguraTransação segura

A Ubuy trabalha arduamente para proteger a sua segurança e privacidade. O nosso sistema avançado de segurança de pagamentos garante a confidencialidade ao encriptar as suas informações durante a transmissão, utilizando os protocolos AES (Normas de Encriptação Avançada) e SSL (Camada de Sockets Seguros). Os seus dados de pagamento estão 100% seguros, pois não partilhamos os seus dados de pagamento com vendedores terceiros.

Os nossos principais Parceiros Logísticos
  • fedex
  • dhl
Transform your machine learning projects into successful deployments with this practical guide on how to build and scale solutions that solve real-world problems
Garantia U-Care:
Nenhuma
Selecione um plano
fast shipping

Fast
Shipping

free return

Devolução
gratuita*

Embalagem Segura

Embalagem Segura

Produtos 100% Originais

Produtos 100% Originais

pci-dss

Certificação PCI DSS

iso certified

Certificação ISO 27001

paypal payment
visa payment
mastercard payment
Note: Step Down Voltage Transformer required for using electronics products of EUA store (110-120). Recommended power converters COMPRAR AGORA.

O que se Destaca

Practical MLOps Guide
This book offers real-world examples, making complex MLOps concepts accessible and applicable, enabling readers to effectively manage the lifecycle of machine learning models.
Conteúdo atualizado
The second edition includes the latest developments in machine learning and MLOps, ensuring that readers have relevant and current insights into industry practices.
Comprehensive Learning
Covering both foundational and advanced topics, this book equips readers with the necessary skills to implement, monitor, and maintain machine learning solutions in various environments.

Detalhes do produto

Shop Machine Learning Engineering with Python: Manage the lifecycle of machine learning models using MLOps with practical examples online at a best price in Angola. 1837631964
EditoraPackt Publishing
Data de publicaçãoAugust 31, 2023
Edição2nd
IdiomaInglês
Comprimento de impressão 462 pages
ISBN-10 1837631964
ISBN-13 978-1837631964
Peso do Item1,74 libras (790 gramas)
Dimensões7.5 x 1.05 x 9.25 inches (19.1 x 2.7 x 23.5 cm)

Quem Deverá Comprar?

Suitable For
  • Aspiring Data Scientists

    Those entering the field will benefit from structured learning and practical examples to build foundational skills.

  • ML Engineers

    Current professionals aiming to enhance their MLOps knowledge and workflows will find valuable insights and techniques.

  • Project Managers

    Individuals overseeing ML projects will gain an understanding of model lifecycle and MLOps integration for better management.

Not Suitable For
  • Iniciantes Completos

    Readers with no prior knowledge of machine learning may find the book's concepts too advanced or confusing.

DESCRIÇÃO DO PRODUTO

Machine Learning Engineering with Python: Manage the lifecycle of machine learning models using MLOps with practical examples

Tem alguma Dúvida? Converse connosco

Perguntas e respostas do cliente

  • Pergunta: What is 'Machine Learning Engineering with Python' about?

    Resposta: The book 'Machine Learning Engineering with Python' focuses on effectively managing the lifecycle of machine learning models, particularly through the lens of MLOps. It provides a comprehensive guide on deploying, maintaining, and optimizing machine learning systems. Practical examples throughout the book help bridge the gap between theory and application. Whether you are a beginner or experienced in ML, the content is structured to enhance your understanding of model production and maintenance, making it an essential resource for anyone looking to implement ML solutions in real-world scenarios.
  • Pergunta: Who is the target audience for this book?

    Resposta: This book targets machine learning practitioners, data scientists, and software engineers looking to deepen their understanding of MLOps. It caters to both beginners and those with some experience in machine learning, making it a valuable resource for professionals seeking to streamline their model deployment and management processes. The content is designed to be practical, ensuring that readers can directly apply the concepts in their organizations or personal projects, facilitating a smooth transition from development to production.
  • Pergunta: What practical examples does this book provide?

    Resposta: The book offers a variety of practical examples that illustrate key concepts in managing machine learning models. These examples range from end-to-end project walkthroughs to real-case scenarios showcasing how to implement MLOps practices efficiently. Readers can expect to find step-by-step guides for deploying models, monitoring performance, and iterating designs based on real-world data. This hands-on approach not only makes the complex themes of ML more digestible but also prepares readers for the challenges they may encounter in their projects.
  • Pergunta: How does this book differ from other machine learning books?

    Resposta: Unlike many traditional machine learning books that focus heavily on algorithms and theory, 'Machine Learning Engineering with Python' emphasizes the lifecycle and operational aspects of ML models. This focus on MLOps as a discipline equips readers with a framework for deploying and managing their models effectively. The real-world examples and practical advice provided make it unique in helping professionals understand not just how to build models, but how to maintain and optimize them in production environments, setting it apart from more theoretical texts.
  • Pergunta: What are the key topics covered in this edition?

    Resposta: The 2nd edition covers an extensive range of topics crucial for machine learning engineering, including data preprocessing, model deployment, performance monitoring, and continuous integration & delivery in ML workflows. It also addresses the evolving landscape of tools and technologies in MLOps, such as cloud services and automated pipelines. Each topic is designed to provide readers with a thorough understanding of how to take ML models from development to deployment while ensuring scalability and reliability, making it a timely resource in the fast-paced field of AI.
  • Pergunta: What are the prerequisites for reading this book?

    Resposta: While the book is accessible to readers with basic Python programming skills, having a foundational understanding of machine learning concepts and practices is beneficial. Familiarity with libraries like Pandas, NumPy, and Scikit-learn will enhance comprehension. Those who have worked on machine learning projects will find it easier to grasp the operational aspects and practical applications discussed. This makes it ideal for professionals wanting to improve their skill set or students aiming to enter the field of machine learning engineering.
  • Pergunta: How can I implement MLOps practices described in the book?

    Resposta: To implement the MLOps practices described in the book, start by setting up an agile and collaborative environment in your organization. Use the provided frameworks and roadmaps to develop a structured pipeline for model training, deployment, and monitoring. The practical examples serve as templates to guide your implementations. For instance, you can begin with small-scale projects, gradually applying the principles of version control and automated testing as you gain confidence. This approach not only leads to improved model performance but also enhances team collaboration.
  • Pergunta: Is there any online content that accompanies the book?

    Resposta: Yes, the authors often provide supplementary materials and resources on their website or through online platforms associated with the book. These may include access to code examples, datasets for practice, and updates relevant to the latest trends in machine learning and MLOps. Engaging with the online content can enrich your learning experience by offering interactive elements that reinforce the concepts discussed in the book, making it easier to apply them to real-world situations.
  • Pergunta: What are some common challenges faced in machine learning engineering?

    Resposta: Common challenges in machine learning engineering include model deployment complexities, data quality issues, and maintaining model performance over time. Other obstacles often involve integration with existing systems and managing resource allocation efficiently. The book addresses these challenges by providing strategies to mitigate them, such as implementing robust data handling practices and establishing effective monitoring systems. By following the methodologies described in the text, readers can better navigate these challenges and improve the resilience and reliability of their ML systems.
  • Pergunta: Where can I buy 'Machine Learning Engineering with Python'?

    Resposta: You can purchase 'Machine Learning Engineering with Python: Manage the lifecycle of machine learning models using MLOps with practical examples 2nd Edition' on Ubuy. Ubuy offers a reliable platform for acquiring the book, ensuring that you get your copy quickly and efficiently. Whether you're looking to improve your skills in machine learning engineering or seeking practical insights into MLOps, this edition is a great addition to your library.

Neural Networks Editorial Review

"Machine Learning Engineering with Python: Manage the lifecycle of machine learning models using MLOps with practical examples" is a must-have book for anyone looking to improve their knowledge of machine learning. The book provides a detailed description of concepts and includes practical examples and screenshots to make it an interactive learning experience. One of the strengths of this book is that it is suitable for beginners, as it starts with definitions of career tracks and provides guidance on effective teamwork. It covers the entire lifecycle of MLOps, making it a valuable resource for those looking to kick-start their career in this field. The organization and table of contents are well-designed, and the preface accurately sets the tone for the rest of the book. The author's attention to detail and writing style provide assurance to the reader. The book can be divided into three acts - introduction, details, and full example. The introduction explains the basics of MLE and familiarizes the reader with the tools and languages used in this field. The second act provides in-depth details and examples, allowing the reader to grasp the content effectively. The final act brings together all the knowledge learned and presents a complete example. Overall, this book is well-written and serves as a great starting point for those interested in MLE. It is recommended to have prior knowledge of Python and ML techniques to fully benefit from the book's content.

Avaliações e Classificações dos Clientes

1 classificações de clientes
  • 5 Estrela
    0%
  • 4 Estrela
    100%
  • 3 Estrela
    0%
  • 2 Estrela
    0%
  • 1 Estrela
    0%

Avaliar este produto

Partilhe as suas ideias com outros clientes

Prós

  • Detailed description of concepts with practical examples and screenshots
  • Suitable for beginners and provides guidance on effective teamwork
  • Well-organized and well-designed table of contents
  • Provides in-depth details and examples for effective learning
  • Presents a complete example to reinforce knowledge

Contras

  • Assumes prior knowledge of Python and ML techniques

CONFIANÇA NA PLATAFORMA E SEGURANÇA DO COMPRADOR

trustpilot logo
4.2/5 9250 + reviews
Ler avaliações
MA
Mohammad
Comprador verificado

“Excellent quality and original too,when ubuy send original things I will appreciate that ,I very satisfied thank you”

23 July 2026 · via Trustpilot
CK
Chitra
Comprador verificado

“The order and delivery progress was communicated very well. Package arrived within the estimated time. Products arrived as expected in good condition.”

22-Jul-26 · via Trustpilot
K
kund
Comprador verificado

“Good supply of products. Safe payment methods, and shipment worldwide! Genuine products.”

23-Jul-26 · via Trustpilot
OO
Onesi
Comprador verificado

“Was my first time buying a product from Ubuy, but I found it so helpful. This is reliable. Gonna place a new order!”

22 July 2026 · via Trustpilot
SJ
SAO JOHN
Comprador verificado

“Ubuy is a great online platform to buy stuff. Reliable, fast delivery time and great value for money. I've been using Ubuy online shopping platform for three years now and will continue to do so.”

23 July 2026 · via Trustpilot
Checkout Seguro Entrega Global Devoluções Fáceis Produtos Genuínos

Informação importante

  • Limitações: para produtos expedidos internacionalmente, tenha em atenção que qualquer garantia do fabricante pode não ser válida; opções de serviço do fabricante podem não estar disponíveis; manuais de produtos, instruções e avisos de segurança podem não estar nas línguas do país de destino; os produtos (e materiais que o acompanham) pode não ter sido concebido em conformidade com as normas, especificações e requisitos de rotulagem do país de destino; e os produtos podem não estar em conformidade com a voltagem e outras normas elétricas do país de destino (requerendo assim o uso de um adaptador ou conversor caso seja apropriado). O destinatário é responsável por garantir que o produto pode ser legalmente importado para o país de destino. Quando encomenda à Ubuy ou aos seus afiliados, o destinatário é o importador de registo e deve estar em conformidade com todas as leis e regulamentos do país de destino.
  • Nem todos os produtos listados na Ubuy estão à venda, uma vez que a Ubuy é um motor de busca global. Os produtos estão sujeitos a leis de exportação/comércio.

AOA 55457

Encomende já e receba por volta de Sexta-Feira, Agosto 28

Qtd.:

Transação seguraTransação segura

Em conformidade com a norma PCI DSS e com certificação ISO 27001:2022, com pagamentos encriptados e proteção total do comprador em todas as encomendas.

Os nossos principais Parceiros Logísticos
  • fedex
  • dhl
Entrega internacional mais rápida

Recursos e benefícios

  • Learn practical problem-solving skills
  • Deep dive into ML fundamentals
  • Explore best practices for ML engineering
  • Automate training and deployment processes
  • Build wrapper libraries for encapsulating ML logic
  • Test yourself through real-world scenarios

Ubuy Assurance

Experience worry-free shopping with 100% original products, PCI DSS-compliant payment security, ISO 27001-certified data protection, the fastest cross-border delivery, free returns *, and secure packaging on every order.