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Machine Learning System Design: With End-To-End Examples

Description:

Get the big picture and the important details with this end-to-end guide for designing highly effective, reliable machine learning systems.

In
Machine Learning System Design: With end-to-end examples you will learn:

  • The big picture of machine learning system design
  • Analyzing a problem space to identify the optimal ML solution
  • Ace ML system design interviews
  • Selecting appropriate metrics and evaluation criteria
  • Prioritizing tasks at different stages of ML system design
  • Solving dataset-related problems through data gathering, error analysis, and feature engineering
  • Recognizing common pitfalls in ML system development
  • Designing ML systems to be lean, maintainable, and extensible over time


Machine Learning System Design: With end-to-end examples is a practical guide for planning and designing successful ML applications. It lays out a clear, repeatable framework for building, maintaining, and improving systems at any scale. Authors Arseny Kravchenko and Valeri Babushkin have filled this unique handbook with campfire stories and personal tips from their own extensive careers. You'll learn directly from their experience as you consider every facet of a machine learning system, from requirements gathering and data sourcing to deployment and management of the finished system.


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.

Valerii Babushkin is an accomplished data science leader with extensive experience in the tech industry. He currently serves as the VP of Data Science at Blockchain.com, where he is responsible for leading the company's data-driven initiatives. Prior to joining Blockchain.com, Valerii held key roles at leading tech companies, such as Facebook, Alibaba, and X5 Retail Group.

Details:

Machine Learning System Design: With End-To-End Examples

Product ID: K1633438759
Condition: New

BHD3386

Price includes VAT & Import Duties
Type: Paperback
Availability: In Stock

Quantity:

|

Order today to get by 7-14 business days

This item qualifies for free delivery

Returns & Warranty policies

Imported From: United Kingdom

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.

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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.

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Machine Learning System Design: With End-To-End Examples

Product ID: K1633438759
Condition: New
Machine Learning System Design: With End-To-End Examples-0
Type: Paperback

BHD3386

Price includes VAT & Import Duties
Availability: In Stock

Quantity:

|

Order today to get by 7-14 business days

This item qualifies for free delivery

Returns & Warranty policies

Imported From: United Kingdom

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:

Get the big picture and the important details with this end-to-end guide for designing highly effective, reliable machine learning systems.

In
Machine Learning System Design: With end-to-end examples you will learn:

  • The big picture of machine learning system design
  • Analyzing a problem space to identify the optimal ML solution
  • Ace ML system design interviews
  • Selecting appropriate metrics and evaluation criteria
  • Prioritizing tasks at different stages of ML system design
  • Solving dataset-related problems through data gathering, error analysis, and feature engineering
  • Recognizing common pitfalls in ML system development
  • Designing ML systems to be lean, maintainable, and extensible over time


Machine Learning System Design: With end-to-end examples is a practical guide for planning and designing successful ML applications. It lays out a clear, repeatable framework for building, maintaining, and improving systems at any scale. Authors Arseny Kravchenko and Valeri Babushkin have filled this unique handbook with campfire stories and personal tips from their own extensive careers. You'll learn directly from their experience as you consider every facet of a machine learning system, from requirements gathering and data sourcing to deployment and management of the finished system.


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.

Valerii Babushkin is an accomplished data science leader with extensive experience in the tech industry. He currently serves as the VP of Data Science at Blockchain.com, where he is responsible for leading the company's data-driven initiatives. Prior to joining Blockchain.com, Valerii held key roles at leading tech companies, such as Facebook, Alibaba, and X5 Retail Group.

Details:

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