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Automated Machine Learning: Hyperparameter optimization, neural architecture search, and algorithm selection with cloud platforms
By the end of this machine learning book, you'll be able to build and deploy AutoML models that are not only accurate, but also increase productivity, allow interoperability, and minimize feature engineering tasks.
Automated Machine Learning: Hyperparameter optimization, neural architecture search, and algorithm selection with cloud platforms
Artikal br.: 34827171

Automated Machine Learning: Hyperparameter optimization, neural architecture search, and algorithm selection with cloud platforms

Artikal br.: 34827171

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By the end of this machine learning book, you'll be able to build and deploy AutoML models that are not only accurate, but also increase productivity, allow interoperability, and minimize feature engineering tasks.
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What Stands Out

Hyperparameter Optimization
Efficiently fine-tune model parameters to achieve optimal performance, reducing time spent on manual adjustments and enhancing predictive accuracy.
Neural Architecture Search
Automated exploration of neural network designs to discover innovative structures, streamlining development and improving model capability without extensive human intervention.
Cloud Integration
Seamlessly leverage cloud platforms for scalable computing power, enabling rapid experimentation and deployment of machine learning models while minimizing IT overhead.

Detalji o proizvodu

Shop Automated Machine Learning: Hyperparameter optimization, neural architecture search, and algorithm selection with cloud platforms online at a best price in Bosnia and Herzegovina. 1800567685
  • Automate machine learning tasks with AutoML
  • Learn how to optimize hyperparameters and neural architecture
  • Implement AutoML using open source tools or cloud platforms
  • Reduce human errors and save time in machine learning models
  • Make machine learning accessible for all users
  • Increase productivity and minimize feature engineering tasks
Publisher Packt Publishing
Publication date February 18, 2021
Language English
Print length 312 pages
ISBN-10 1800567685
ISBN-13 978-1800567689
Item Weight 1.19 pounds (540 grams)
Dimensions 7.5 x 0.71 x 9.25 inches (19.1 x 1.8 x 23.5 cm)

Who Should Buy?

Suitable For
  • Data Scientists

    Data scientists can streamline model training processes, saving time and enhancing productivity using automated machine learning features.

  • Organizations with Limited Resources

    Small businesses without extensive ML expertise can use this product to implement machine learning without hiring specialists.

  • Researchers

    Researchers can quickly run experiments, optimizing algorithms and architectures for better performance and faster iterations.

Not Suitable For
  • Beginner Users

    Users lacking basic understanding of machine learning concepts may struggle to effectively leverage the product's capabilities.

OPIS PROIZVODA

Automated Machine Learning: Hyperparameter optimization, neural architecture search, and algorithm selection with cloud platforms

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Pitanja i odgovori kupaca

  • Pitanje: Kako kupovati Automated Machine Learning: Hyperparameter online od Ubuya?

    Odgovor: Lako je kupovati Automated Machine Learning: Hyperparameter online od Ubuya.. Vi samo trebate potražiti proizvod, odabrati način dostave prilikom odjavljivanja i dostaviti ga na vašu lokaciju.
  • Pitanje: Je li Automated Machine Learning: Hyperparameter dostupan za online kupovinu u Bosnia and Herzegovina?

    Odgovor: Da, u Ubuy Bosnia and Herzegovina ovaj proizvod je dostupan za kupovinu po razumnoj cijeni.. Automated Machine Learning: Hyperparameter nije dostupan lokalno, ali možete nam povjeriti naše usluge ekspresne dostave.
  • Pitanje: Koliko vremena je potrebno da dobijete proizvod nakon narudžbe?

    Odgovor: Vrijeme isporuke vašeg naručenog proizvoda ovisi o tome šta ste naručili i načinu dostave koji ste odabrali.. Predviđeno vrijeme dostave se spominje prilikom naplate, stoga budite bezbrižni prilikom kupovine.

Expert Systems Editorial Review

**** "Automated Machine Learning" serves as an invaluable resource for beginners and intermediate users who are eager to explore the rapidly evolving field of automated machine learning (AutoML). The manuscript exhibits a well-organized approach, delving into both open-source and commercially available AutoML options from major cloud platforms including Azure, AWS, and Google Cloud. It provides a comprehensive overview of the state of the AutoML ecosystem, illustrating its growing relevance in modern AI applications. Readers commend the book for its breadth of knowledge and systematic structure, which covers the essentials of AutoML without diving deeply into the basics of machine learning, Python programming, or cloud environments. This makes it particularly beneficial for those with some foundational understanding who wish to expedite their learning process and automate tedious tasks in their machine learning workflows. Key strengths of the book include its practical, hands-on examples using popular datasets, which provide users concrete instances of how to implement AutoML systems. Furthermore, the inclusion of various frameworks, process flow diagrams, and tables enhance the comparative analysis of different AutoML options, clarifying the complexities of the subject matter. While the book shines in many respects, it is noted that the examples are mostly centered around simpler datasets, and readers would appreciate more challenging use cases to enrich their learning experience. Additionally, the reliance on screenshots, although helpful, poses a challenge as readers voice concern regarding their longevity and potential obsolescence as cloud platforms evolve. Overall, "Automated Machine Learning" is highly recommended for AI practitioners looking to embrace automation in their machine learning processes while providing a thorough exploration of available tools and frameworks. **

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Pros

  • Comprehensive overview of AutoML options across major cloud platforms and open-source systems.
  • Well-structured approach that aids beginners in grasping complex concepts.
  • Hands-on examples with practical applications using popular datasets.
  • Visual aids enhance understanding and facilitate comparison of AutoML options.
  • Engaging writing style with humorous elements makes for enjoyable reading.

Cons

  • Focus on simpler datasets may limit exposure to more complex use cases.

Product Price History

Važna informacija

  • Ograničenja: Za proizvode koji se isporučuju na međunarodnom nivou, molimo imajte na umu da garancija proizvođača možda neće biti važeća, da opcije usluga servisiranja od strane proizvođača možda neće biti dostupne, da priručnici za proizvode, uputstva i sigurnosna upozorenja možda nisu na jezicima odredišne ​​zemlje, da proizvodi (i prateći materijali) možda nisu dizajnirani u skladu sa standardima zemlje odredišta, specifikacijama i pravilima za označavanje i da proizvodi možda nisu u skladu sa naponom koji se koristi u zemlji odredišta i drugim električnim standardima (što bi zahtijevalo upotrebu adaptera ili pretvarača po potrebi). Primalac je odgovoran da provjeri da li se proizvod može legalno uvesti u zemlju odredišta. Kada naručuje sa Ubuy, primalac je uvoznik na formularima i mora se pridržavati svih zakona i propisa zemlje odredišta.
  • Nisu svi proizvodi navedeni na Ubuy-u na prodaju jer je Ubuy globalna tražilica. Proizvodi podliježu izvozno/trgovačkim propisima.