Reliable Machine Learning: Applying SRE Principles to ML in Production

Similar books (20)

• 

  AI Engineering: Building Applications with Foundation Models

  Recent breakthroughs in AI have not only increased demand for AI products, they've also lowered the barriers to entry for those who want to build AI products. The model-as-a-service approach has trans…

  Buy this book on Amazon
• 

  Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications

  Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with dat…

  Buy this book on Amazon
• 

  The Engineering Executive's Primer: Impactful Technical Leadership

  As an engineering manager, you almost always have someone in your company to turn to for a peer on another team, your manager, or even the head of engineering. But who do you turn to if you're the hea…

  Buy this book on Amazon
• 

  System Design Interview – An insider's guide

  The system design interview is considered to be the most complex and most difficult technical job interview by many. This book provides a step-by-step framework on how to tackle a system design questi…

  Buy this book on Amazon
• 

  Chip War: The Fight for the World's Most Critical Technology

  An epic account of the decades-long battle to control what has emerged as the world's most critical resource—microchip technology—with the United States and China increasingly in conflict.
  
  You may be s…

  Buy this book on Amazon
• 

  Build a Large Language Model

  Buy this book on Amazon
• 

  Thinking, Fast and Slow

  In the highly anticipated Thinking, Fast and Slow, Kahneman takes us on a groundbreaking tour of the mind and explains the two systems that drive the way we think. System 1 is fast, intuitive, and emo…

  Buy this book on Amazon
• 

  Software Architecture: The Hard Parts: Modern Trade-Off Analyses for Distributed Architectures

  There are no easy decisions in software architecture. Instead, there are many hard parts--difficult problems or issues with no best practices--that force you to choose among various compromises. With …

  Buy this book on Amazon
• 

  Team Topologies: Organizing Business and Technology Teams for Fast Flow

  
  Effective software teams are essential for any organization to deliver value continuously and sustainably. But how do you build the best team organization for your specific goals, culture, and needs? …

  Buy this book on Amazon
• 

  Introducing MLOps: How to Scale Machine Learning in the Enterprise

  Buy this book on Amazon
• 

  The Manager's Path: A Guide for Tech Leaders Navigating Growth and Change

  Managing people is difficult wherever you work, but the tech industry as a whole is pretty bad at it. Tech companies in general lack the experience, tools, texts, and frameworks to do it well. And the…

  Buy this book on Amazon
• 

  Leonardo da Vinci

  Based on thousands of pages from Leonardo's astonishing notebooks and new discoveries about his life and work, Walter Isaacson weaves a narrative that connects his art to his science. He shows how Leo…

  Buy this book on Amazon
• 

  Hands-On Machine Learning with Scikit-Learn and TensorFlow

  A series of Deep Learning breakthroughs have boosted the whole field of machine learning over the last decade. Now that machine learning is thriving, even programmers who know close to nothing about t…

  Buy this book on Amazon
• 

  The Pragmatic Programmer: From Journeyman to Master

  Straight from the programming trenches, The Pragmatic Programmer cuts through the increasing specialization and technicalities of modern software development to examine the core process--taking a …

  Buy this book on Amazon
• 

  The Software Engineer's Guidebook: Navigating senior, tech lead, and staff engineer positions at tech companies and startups

  Buy this book on Amazon
• 

  Nexus: A Brief History of Information Networks from the Stone Age to AI

  From the author of Sapiens comes the groundbreaking story of how information networks have made, and unmade, our world.
  
  For the last 100,000 years, we Sapiens have accumulated enormous power. But despi…

  Buy this book on Amazon
• 

  Effective Data Science Infrastructure: How to make data scientists productive

  Buy this book on Amazon
• 

  Building Machine Learning Pipelines: Automating Model Life Cycles with TensorFlow

  Buy this book on Amazon
• 

  Fundamentals of Data Engineering: Plan and Build Robust Data Systems

  Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'l…

  Buy this book on Amazon
• 

  Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps

  The design patterns in this book capture best practices and solutions to recurring problems in machine learning. Authors Valliappa Lakshmanan, Sara Robinson, and Michael Munn catalog the first tried-a…

  Buy this book on Amazon