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35121987
Building Machine Learning Pipelines: Automating Model Life Cycles with Tensorflow (Paperback)
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Item #:
35121987
CAD 106
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What Stands Out
Comprehensive Guidance
Offers in-depth tutorials on automating the machine learning lifecycle, making it accessible for both beginners and experienced practitioners seeking to enhance their workflows.
Hands-On Projects
Includes practical projects that demonstrate real-world applications of TensorFlow, fostering hands-on learning and improving retention of complex concepts essential for mastering ML pipelines.
Expert Insights
Features contributions from industry experts, providing invaluable insights and best practices that help users avoid common pitfalls and enhance their machine learning implementations.
Product Details
- Learn to automate machine learning pipelines using the TensorFlow ecosystem
- Discover techniques to cut deployment time from days to minutes
- Utilize components from TensorFlow Extended to build your pipeline
- Orchestrate your pipeline with Apache Beam, Apache Airflow, and Kubeflow Pipelines
- Work with data using TensorFlow Data Validation and TensorFlow Transform
- Explore model analysis, fairness, bias, and deployment with TensorFlow tools
| Publication date | August, 2020 |
| Author | Hannes Hapke; Catherine Nelson |
| Book format | Paperback |
| Genre | Computing & Internet |
| Pages | 364 |
| Age group | Adult |
| Binding type | Perfect Binding |
| Fiction/nonfiction | Non-Fiction |
| Publisher | O'Reilly Media |
| Reading level | Professional & Vocational |
| Subgenre | Computers |
| Original languages | English |
| Bisac subject heading | Computers |
| Edition | 1st Edition |
| Language | English |
| Pub date | 2020-08-04 |
| Item Weight | 1 lbs (450 grams) |
Who Should Buy?
-
Data Scientists
Ideal for data scientists seeking to automate and streamline machine learning model workflows using TensorFlow effectively.
-
Machine Learning Engineers
Great resource for ML engineers focused on implementing robust pipelines and managing model life cycles efficiently.
-
Students and Learners
Beneficial for students eager to understand the practical application of TensorFlow in building machine learning pipelines.
-
Complete Beginners
Not suitable for individuals without prior knowledge of machine learning concepts or programming skills.
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Hannes Hapke; Catherine Nelson All Books Editorial Review
Building Machine Learning Pipelines: Automating Model Life Cycles with Tensorflow is a comprehensive paperback guide that explores the intricacies of automating model life cycles exclusively using TensorFlow. This non-fiction book, published by O'Reilly Media in August 2020, spans 364 pages and is designed for professionals in computing and internet sectors. With a focus on practical applications, it elaborates on building efficient machine learning pipelines, making it a must-have for those seeking to enhance their technical skills. Additionally, readers will appreciate the clear writing style, which simplifies complex concepts, making the material more accessible for vocational learners.
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Pros
- Comprehensive guide for automating ML processes
- Focuses on practical applications of TensorFlow
- Suitable for professional and vocational readers
- Detailed explanations of machine learning pipelines
- 1st edition with updated content
Cons
- Some might find the content too technical initially
Product Price History
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Features & Benefits
- Automate a machine learning pipeline
- Cut deployment time from days to minutes
- Focus on developing new models rather than maintaining legacy systems
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