Machine Learning Engineering with Python: Manage the production life cycle of machine learning models using MLOps with practical examples
Supercharge the value of your machine learning models by building scalable and robust solutions that can serve them in production environments.
Machine Learning Engineering with Python: Manage the production life cycle of machine learning models using MLOps with practical examples
Articol nr.: 45099508

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

Articol nr.: 45099508

RON 294

Price Details

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

*All items will import from SUA

Nu este pe stoc
SUA Importat din USA
partenerii noștri principali de logistică
  • fedex
  • dhl
Supercharge the value of your machine learning models by building scalable and robust solutions that can serve them in production environments.
Garanție U-Care:
Niciunul
Selectați un plan
fast shipping

Fast
Shipping

free return

Retur
gratuit*

Ambalaj sigur

Ambalaj sigur

Produse originale 100%

Produse originale 100%

pci-dss

PCI DSS Compliance

iso certified

ISO 27001 Certified


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

Detalii produs

Learn how to manage the production life cycle of machine learning models using MLOps techniques. Get practical examples and master Python! Shop at Ubuy Romania
Item Weight2 lbs (910 grams)

DESCRIEREA PRODUSULUI

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

Aveți Întrebări? Discutați cu noi

Întrebări și răspunsuri ale clienților

  • întrebare: Who is the target audience for this book?

    Răspuns: This book is for machine learning engineers, data scientists, and software developers who want to build robust software solutions with machine learning components. Intermediate-level knowledge of Python is necessary.
  • întrebare: What will I learn from this book?

    Răspuns: You will learn how to build scalable and robust solutions that can serve your machine learning models in production environments, including hyperparameter optimization, model management, building ML libraries and packages, exploring ML engineering patterns, toolsets for training and deployment, and using cloud-based tools.
  • întrebare: Does the book include practical examples?

    Răspuns: Yes, the book includes practical illustrations and examples to help you solve typical business problems.

Computer Science Editorial Review

**** "Machine Learning Engineering with Python" emerges as a pivotal resource for intermediate data scientists and ML engineers seeking a deeper understanding of machine learning implementation in real-world scenarios. Unlike many books that concentrate on theoretical models or isolated ML frameworks, this guide emphasizes practical applications and essential MLops tools that enhance the ability to train, deploy, serve, and iterate on models effectively. The author successfully addresses a significant gap in the understanding of implementation techniques by integrating multiple real-time and batch example scenarios. These practical illustrations not only elucidate critical areas such as versioning, model retraining due to data drift, and automation of hyperparameters, but also dive into deployment and scaling methodologies—particularly noteworthy in chapters on deployment patterns and scaling strategies. Readers have found value in the clarity of explanations, visual aids like diagrams, and organized breakdowns of complex concepts, making it easier to absorb information. Furthermore, the book's repository, offering example datasets and code in Python notebooks, has been a highlight for many, facilitating hands-on learning and practical application. However, some critiques have surfaced regarding the book's focus on AWS for deployment, potentially alienating users of Azure or Google Cloud. Additionally, the end-to-end examples presented may not fully encapsulate the detailed coding necessary for newcomers, suggesting an area for improvement for future editions. Overall, the book serves as an excellent guide into the practical aspects of machine learning engineering, making it a compelling read for professionals eager to enhance their skillset and implement ML solutions in their organizations effectively. **

Recenziile și evaluările clienților

5.0
1 evaluări ale clienților
  • 5 stele
    100%
  • 4 stele
    0%
  • 3 stele
    0%
  • 2 stele
    0%
  • 1 stele
    0%

Faceți o recenzie pentru acest produs

Spuneți-vă părerile și altor clienți

Pro

  • Comprehensive coverage of MLops tools and real-world applications.
  • Good balance of theory and practical exercises, especially for intermediate users.
  • Clear and detailed explanations of deployment patterns and scaling strategies.
  • Helpful visual aids enhance understanding.
  • Useful repositories with datasets and code examples.

Contra

  • Limited focus on cloud platforms other than AWS might exclude some readers.

Istoric de Preț al Produsului

Important

  • Limite: Pentru produsele expediate la nivel internațional, vă rugăm să rețineți că este posibil ca garanția producătorului să nu fie valabilă; este posibil ca opțiunile de service ale producătorului să nu fie disponibile; este posibil ca manualele, instrucțiunile și avertismentele de siguranță ale produsului să nu fie în limba țării de destinație; este posibil ca produsele (și materialele însoțitoare) să nu fie proiectate în conformitate cu standardele, specificațiile și cerințele privind etichetarea din țara de destinație; este posibil ca produsele să nu fie conforme cu voltajul și cu alte standarde electrice din țara de destinație (necesitând utilizarea unui adaptor sau convertor, dacă este cazul). Destinatarul este responsabil pentru asigurarea faptului că produsul poate fi importat legal în țara de destinație. Când comandați de pe Ubuy sau de la afiliații acestuia, destinatarul este importatorul înregistrat și trebuie să respecte toate legile și reglementările din țara de destinație
  • Nu toate produsele listate pe Ubuy sunt de vânzare, deoarece Ubuy este un motor de căutare global. Produsele sunt supuse reglementărilor privind exportul/comerțul.