Title
Data Science On Aws: Implementing Endtoend, Continuous Ai And Machine Learning Pipelines
Delivery time: 8-12 business days (International)
With This Practical Book, Ai And Machine Learning Practitioners Will Learn How To Successfully Build And Deploy Data Science Projects On Amazon Web Services. The Amazon Ai And Machine Learning Stack Unifies Data Science, Data Engineering, And Application Development To Help Level Up Your Skills. This Guide Shows You How To Build And Run Pipelines In The Cloud, Then Integrate The Results Into Applications In Minutes Instead Of Days. Throughout The Book, Authors Chris Fregly And Antje Barth Demonstrate How To Reduce Cost And Improve Performance. Apply The Amazon Ai And Ml Stack To Realworld Use Cases For Natural Language Processing, Computer Vision, Fraud Detection, Conversational Devices, And More Use Automated Machine Learning To Implement A Specific Subset Of Use Cases With Sagemaker Autopilot Dive Deep Into The Complete Model Development Lifecycle For A Bertbased Nlp Use Case Including Data Ingestion, Analysis, Model Training, And Deployment Tie Everything Together Into A Repeatable Machine Learning Operations Pipeline Explore Realtime Ml, Anomaly Detection, And Streaming Analytics On Data Streams With Amazon Kinesis And Managed Streaming For Apache Kafka Learn Security Best Practices For Data Science Projects And Workflows Including Identity And Access Management, Authentication, Authorization, And More
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⚠️ WARNING (California Proposition 65):
This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.
For more information, please visit www.P65Warnings.ca.gov.
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To facilitate a smooth return process, a Return Authorization (RA) Number is required for all returns. Returns without a valid RA number will be declined and may incur additional fees. You can request an RA number within 15 days of the original delivery date. For more details, please refer to our Return & Refund Policy page.
Shipping & Returns
Shipping
We ship your order within 2–3 business days for USA deliveries and 5–8 business days for international shipments. Once your package has been dispatched from our warehouse, you'll receive an email confirmation with a tracking number, allowing you to track the status of your delivery.
Returns
To facilitate a smooth return process, a Return Authorization (RA) Number is required for all returns. Returns without a valid RA number will be declined and may incur additional fees. You can request an RA number within 15 days of the original delivery date. For more details, please refer to our Return & Refund Policy page.
Warranty
We provide a 2-year limited warranty, from the date of purchase for all our products.
If you believe you have received a defective product, or are experiencing any problems with your product, please contact us.
This warranty strictly does not cover damages that arose from negligence, misuse, wear and tear, or not in accordance with product instructions (dropping the product, etc.).
Warranty
We provide a 2-year limited warranty, from the date of purchase for all our products.
If you believe you have received a defective product, or are experiencing any problems with your product, please contact us.
This warranty strictly does not cover damages that arose from negligence, misuse, wear and tear, or not in accordance with product instructions (dropping the product, etc.).
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Secure Payment
Your payment information is processed securely. We do not store credit card details nor have access to your credit card information.
We accept payments with :
Visa, MasterCard, American Express, Paypal, Shopify Payments, Shop Pay and more.
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Frequently Asked Questions
- Q: What topics are covered in 'Data Science on AWS'? A: The book covers a range of topics including building and deploying data science projects on Amazon Web Services, data engineering, application development, and the complete model development lifecycle for natural language processing and other AI applications.
- Q: Who is the intended audience for this book? A: This book is aimed at AI and machine learning practitioners, data scientists, and anyone interested in implementing data science projects using AWS.
- Q: How many pages is the book? A: The book has 521 pages, providing an in-depth exploration of data science on AWS.
- Q: What format is the book available in? A: The book is available in paperback format.
- Q: When was 'Data Science on AWS' published? A: The book was published on May 11, 2021.
- Q: Does this book include practical examples? A: Yes, the book includes real-world use cases and practical examples to help readers understand how to apply the Amazon AI and ML stack effectively.
- Q: What machine learning services does the book discuss? A: The book discusses various AWS services including SageMaker Autopilot, Amazon Kinesis, and Managed Streaming for Apache Kafka.
- Q: Are there any security best practices mentioned? A: Yes, the book covers security best practices for data science projects, including identity and access management, authentication, and authorization.
- Q: Is this book suitable for beginners in data science? A: While the book provides practical insights, a basic understanding of data science and machine learning concepts is recommended for readers to fully benefit from its content.
- Q: What is the edition of this book? A: This is the first edition of 'Data Science on AWS'.