
From Model Building to MLOps
Iterative System Design Solutions for Scalable, Production-Ready Machine Learning ApplicationsBy Nadia FerreiroLength13h 32m
About this audiobook
A practical guide to designing, deploying and operating production machine learning systems, from framing the prediction task through feature pipelines, serving, monitoring, retraining and MLOps orchestration.
Audiobook details
GenreTechnology
Length13 hrs 32 mins
Narrated byListen with 1,000+ voices
FormateBook with Audio
Publish dateSep 27, 2026
LanguageEnglish
Table of contents
1From Model Building to MLOps
2Foreword
3Preface
4About This Book
5Chapter 1: Framing the Problem
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61.1 From Business Objective to Prediction Task
71.2 Feasibility Checks Before You Build
81.3 Baselines You Must Beat
91.4 When Not to Use Machine Learning
101.5 Scoping the First Iteration
111.6 The System Sketch for This Book
12Chapter 2: Data Systems and Sources
132.1 Batch and Streaming Ingestion
142.2 Warehouses, Lakes and Lakehouses
152.3 Row and Columnar Formats
162.4 Schema Evolution and Contracts
172.5 Data Quality Gates
182.6 The Ingestion System Sketch
19Chapter 3: Training Data
203.1 Sampling Design
213.2 Labelling Strategy
223.3 Weak Supervision and Programmatic Labels
233.4 Class Imbalance
243.5 Leakage and Contamination
253.6 The Training Data System Sketch
26Chapter 4: Features and Feature Stores
274.1 Transformation Pipelines
284.2 Point-in-Time Correctness
294.3 Training-Serving Skew
304.4 Feature Stores and Reuse
314.5 Feature Versioning and Deprecation
324.6 The Feature System Sketch
33Chapter 5: Model Development and Offline Evaluation
345.1 Baselines and Model Selection
355.2 Cross-Validation for Time-Ordered Data
365.3 Calibration
375.4 Slice-Based Evaluation
385.5 Structured Error Analysis
395.6 The Evaluation System Sketch
40Chapter 6: Deployment Patterns
416.1 Batch Scoring
426.2 Online Prediction Services
436.3 Streaming and Near-Real-Time Features
446.4 Edge, Cloud and Hybrid
456.5 Choosing a Pattern
466.6 The Deployment System Sketch
47Chapter 7: Serving Infrastructure
487.1 Containerized Model Services
497.2 Autoscaling and Capacity
507.3 Latency Budgets