Description:
Editorial Reviews
From the Back Cover
From the back cover:
In Machine Learning System Design: With end-to-end examples you'll find a step-by-step framework for creating, implementing, releasing, and maintaining your ML system. Every part of the life cycle is covered, from information gathering to keeping your system well-serviced. Each stage includes its own handy checklist of requirements and is fully illustrated with real-world examples, including interesting anecdotes from the author's own careers.
You'll follow two example companies each building a new ML system, exploring how their needs are expressed in design documents and learning best practices by writing your own. Along the way, you'll learn how to ace ML system design interviews, even at highly competitive FAANG-like companies, and improve existing ML systems by identifying bottlenecks and optimizing system performance.About the reader:
For readers who know the basics of both software engineering and machine learning. Examples in Python.
About the Author
Arseny Kravchenko is a seasoned ML engineer with a proven track record of building and optimizing reliable ML systems for startups, including real-time video processing, manufacturing optimization, and financial transactions analysis.
Details:
Visit the Valerii Babushkin (Author), Arseny Kravchenko (Author) Store
Machine Learning System Design: With end-to-end examples
BHD3094
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Order today to get by 7-14 business days
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Unless otherwise stated, all prices displayed on the product page include applicable taxes and import duties.
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Visit the Valerii Babushkin (Author), Arseny Kravchenko (Author) Store
Machine Learning System Design: With end-to-end examples
BHD3094
Quantity:
Order today to get by 7-14 business days
This item qualifies for free delivery
Imported From: United States
At BOLO, we work hard to ensure the products you receive are new, genuine, and sourced from reputable suppliers.
Every product in the BOLO catalogue is sourced through our Verified Global Supply Network of verified sellers, authorized distributors or directly from the manufacturer.
Each product undergoes thorough inspection and verification at our consolidation and fulfilment centers to ensure it meets our strict authenticity and quality standards before being shipped and delivered to you.
If you ever have concerns regarding the authenticity of a product purchased from us, please contact Bolo Support. We will review your inquiry promptly and, if necessary, provide documentation verifying authenticity or offer a suitable resolution.
Your trust is our top priority, and we are committed to maintaining transparency and integrity in every transaction.
While we strive to display accurate information, variations in packaging, labeling, instructions, or formulation may occasionally occur due to regional differences or supplier updates. For detailed or manufacturer-specific information, please contact the brand directly or reach out to BOLO Support for assistance.
Unless otherwise stated, all prices displayed on the product page include applicable taxes and import duties.
BOLO operates in accordance with the laws and regulations of Bahrain. Any items found to be restricted or prohibited for sale within the Bahrain will be cancelled prior to shipment. We take proactive measures to ensure that only products permitted for sale in Bahrain are listed on our website.
All items are shipped by air, and any products classified as “Dangerous Goods (DG)” under IATA regulations will be removed from the order and cancelled.
All orders are processed manually, and we make every effort to process them promptly once confirmed. Products cancelled due to the above reasons will be permanently removed from listings across the website.
Description:
Editorial Reviews
From the Back Cover
From the back cover:
In Machine Learning System Design: With end-to-end examples you'll find a step-by-step framework for creating, implementing, releasing, and maintaining your ML system. Every part of the life cycle is covered, from information gathering to keeping your system well-serviced. Each stage includes its own handy checklist of requirements and is fully illustrated with real-world examples, including interesting anecdotes from the author's own careers.
You'll follow two example companies each building a new ML system, exploring how their needs are expressed in design documents and learning best practices by writing your own. Along the way, you'll learn how to ace ML system design interviews, even at highly competitive FAANG-like companies, and improve existing ML systems by identifying bottlenecks and optimizing system performance.About the reader:
For readers who know the basics of both software engineering and machine learning. Examples in Python.
About the Author
Arseny Kravchenko is a seasoned ML engineer with a proven track record of building and optimizing reliable ML systems for startups, including real-time video processing, manufacturing optimization, and financial transactions analysis.
Details:
Similar suggestions by Bolo
More from this brand
Similar items from “Data Modeling & Design”
Share with
Or share with link
https://www.bolo.bh/products/U1633438759