Building Machine Learning Pipelines: Automating Model Life Cycles with Tensorflow Paperback
€ 65
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Learn the techniques and tools that will cut deployment time from days to minutes
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What Stands Out
Produkto Aprašymas
- Automate machine learning pipeline using TensorFlow ecosystem
- Cut deployment time from days to minutes
- Utilize components from TensorFlow Extended, Apache Beam, Airflow, and Kubeflow Pipelines
- Work with data using TensorFlow Data Validation and Transform
- Analyze model in detail with TensorFlow Model Analysis, examine fairness and bias
- Deploy models with TensorFlow Serving or TensorFlow Lite for mobile devices, learn privacy-preserving techniques
| Book format | Paperback |
| Fiction/nonfiction | Non-Fiction |
| Genre | Computing & Internet |
| Pub date | 2020-08-04 |
| Pages | 364 |
| Reading level | Professional & Vocational |
| Subgenre | Computers |
| Edition | 1st Edition |
| Publisher | O'Reilly Media |
| Original languages | English |
| Language | English |
| Binding type | Perfect Binding |
| Assembled product height | 9.19 in (23.3 cm) |
| Assembled product weight | 1.28 lb (580 grams) |
| Bisac subject heading | Computers |
Who Should Buy?
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Data Scientists
Ideal for data scientists seeking to automate and streamline machine learning model workflows using TensorFlow effectively.
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Machine Learning Engineers
Great resource for ML engineers focused on implementing robust pipelines and managing model life cycles efficiently.
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Students and Learners
Beneficial for students eager to understand the practical application of TensorFlow in building machine learning pipelines.
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Complete Beginners
Not suitable for individuals without prior knowledge of machine learning concepts or programming skills.
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Casual Readers
May not engage casual readers looking for non-technical literature or general overviews in machine learning.
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Business Executives
Less useful for executives seeking high-level strategies rather than technical insights on model development.
PRODUKTO APRAŠYMAS
Building Machine Learning Pipelines: Automating Model Life Cycles with Tensorflow Paperback
Klientų klausimai ir atsakymai
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klausimas:
Who will benefit from this book?
Answer: Data scientists, machine learning engineers, and DevOps engineers -
klausimas:
What are some of the topics covered in the book?
Answer: Machine learning management lifecycle, data pipelines, model analysis, fairness and bias in model performance, privacy-preserving machine learning techniques -
klausimas:
What tools can be used for orchestration?
Answer: Apache Beam, Apache Airflow, and Kubeflow Pipelines
Hannes Hapke; Catherine Nelson All Books Editorial Review
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Argumentai "už"
- Comprehensive guide on ML pipelines
- Practical examples and projects
- Clear explanations for beginners
- Great for automating processes
- Up-to-date information on TensorFlow
Minusai
- Some minor typographical errors.
Product Price History
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Ubuy works hard to protect your security and privacy. Our advanced payment security system ensures confidentiality by encrypting your information during transmission using AES (Advanced Encryption Standards) and SSL (Secure Socket Layer) protocols. Your payment details are 100% secure as we do not share your payment details with third party sellers.
Savybės ir privalumai
- Automate a machine learning pipeline
- Cut deployment time from days to minutes
- Focus on developing new models rather than maintaining legacy systems