Oreilly Machine Learning Engineering in Action

Files Included :

Appendix A Analyzing decision-tree complexity.mp4 (20.02 MB)
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Appendix A Big O(no) and how to think about runtime performance.mp4 (22.16 MB)
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Appendix A Complexity by example.mp4 (34.17 MB)
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Appendix A General algorithmic complexity for ML.mp4 (18.24 MB)
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Appendix B Containers to deal with dependency hell.mp4 (8.68 MB)
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Appendix B Setting up a development environment (1).mp4 (7.53 MB)
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Appendix B Setting up a development environment.mp4 (7.12 MB)
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Chapter 1 Summary.mp4 (2.05 MB)
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Chapter 1 The core tenets of ML engineering.mp4 (61.81 MB)
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Chapter 1 The goals of ML engineering.mp4 (6.48 MB)
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Chapter 1 What is a machine learning engineer.mp4 (24.84 MB)
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Chapter 10 1Naming, structure, and code architecture.mp4 (26.26 MB)
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Chapter 10 Blind to issues Eating exceptions and other bad practices.mp4 (21.27 MB)
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Chapter 10 Excessively nested logic.mp4 (31.57 MB)
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Chapter 10 Standards of coding and creating maintainable ML code.mp4 (12.07 MB)
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Chapter 10 Summary.mp4 (4.88 MB)
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Chapter 10 Tuple unpacking and maintainable alternatives.mp4 (14.22 MB)
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Chapter 10 Use of global mutable objects.mp4 (21.67 MB)
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Chapter 11 Leveraging AB testing for attribution calculations.mp4 (58.58 MB)
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Chapter 11 Model measurement and why it s so important.mp4 (52.83 MB)
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Chapter 11 Summary.mp4 (1.4 MB)
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Chapter 12 Holding on to your gains by watching for drift.mp4 (67.83 MB)
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Chapter 12 Responding to drift.mp4 (25.89 MB)
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Chapter 12 Summary.mp4 (1.27 MB)
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Chapter 13 Do you really want to be the canary Alpha testing and the dangers of the open source coal mine.mp4 (19.43 MB)
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Chapter 13 ML development hubris.mp4 (54.84 MB)
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Chapter 13 Premature generalization, premature optimization, and other bad ways to show how smart you are.mp4 (50.71 MB)
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Chapter 13 Summary.mp4 (5 MB)
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Chapter 13 Technology-driven development vs solution-driven development.mp4 (12.83 MB)
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Chapter 13 Unintentional obfuscation Could you read this if you didn t write it.mp4 (74.92 MB)
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Chapter 14 Avoiding cargo cult ML behavior.mp4 (27.97 MB)
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Chapter 14 Keeping things as simple as possible.mp4 (20.94 MB)
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Chapter 14 Monitoring everything else in the model life cycle.mp4 (16.36 MB)
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Chapter 14 Monitoring your features.mp4 (21.64 MB)
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Chapter 14 Summary.mp4 (6.25 MB)
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Chapter 14 Writing production code.mp4 (72.11 MB)
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Chapter 14 Wireframing ML projects.mp4 (27.3 MB)
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Chapter 15 End user vs internal use testing.mp4 (29.31 MB)
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Chapter 15 Fallbacks and cold starts.mp4 (36.2 MB)
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Chapter 15 Model interpretability.mp4 (41.72 MB)
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Chapter 15 Quality and acceptance testing.mp4 (41.04 MB)
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Chapter 15 Summary.mp4 (4.2 MB)
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Chapter 16 Feature stores.mp4 (33.37 MB)
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Chapter 16 Prediction serving architecture.mp4 (79.68 MB)
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Chapter 16 Production infrastructure.mp4 (34.73 MB)
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Chapter 16 Summary.mp4 (2.5 MB)
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Chapter 2 Co-opting principles of Agile software engineering.mp4 (17.5 MB)
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Chapter 2 Summary.mp4 (3.36 MB)
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Chapter 2 The foundation of ML engineering.mp4 (3.94 MB)
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Chapter 2 Your data science could use some engineering.mp4 (10.83 MB)
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Chapter 2 A foundation of simplicity.mp4 (11.55 MB)
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Chapter 3 Before you model Planning and scoping a project.mp4 (110.62 MB)
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Chapter 3 Summary.mp4 (1.31 MB)
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Chapter 3 Experimental scoping Setting expectations and boundaries.mp4 (80.88 MB)
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Chapter 4 Before you model Communication and logistics of projects.mp4 (131.66 MB)
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Chapter 4 Don t waste our time Meeting with cross-functional teams.mp4 (52.7 MB)
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Chapter 4 Planning for business rules chaos.mp4 (19.9 MB)
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Chapter 4 Setting limits on your experimentation.mp4 (47.48 MB)
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Chapter 4 Summary.mp4 (4.47 MB)
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Chapter 4 Talking about results.mp4 (16.9 MB)
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Chapter 5 Experimentation in action Planning and researching an ML project.mp4 (73.23 MB)
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Chapter 5 Performing experimental prep work.mp4 (76.32 MB)
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Chapter 5 Summary.mp4 (1.73 MB)
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Chapter 6 Experimentation in action Testing and evaluating a project.mp4 (130.17 MB)
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Chapter 6 Summary.mp4 (1.35 MB)
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Chapter 6 Whittling down the possibilities.mp4 (34.89 MB)
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Chapter 7 Choosing the right tech for the platform and the team.mp4 (53.63 MB)
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Chapter 7 Experimentation in action Moving from prototype to MVP.mp4 (64.26 MB)
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Chapter 7 Summary.mp4 (1.69 MB)
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Chapter 8 Experimentation in action Finalizing an MVP with MLflow and runtime optimization.mp4 (46.1 MB)
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Chapter 8 Scalability and concurrency.mp4 (18.82 MB)
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Chapter 8 Summary.mp4 (1.64 MB)
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Chapter 9 Debugging walls of text.mp4 (10.81 MB)
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Chapter 9 Designing modular ML code.mp4 (15.41 MB)
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Chapter 9 Modularity for ML Writing testable and legible code.mp4 (47.85 MB)
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Chapter 9 Summary.mp4 (2.6 MB)
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Chapter 9 Using test-driven development for ML.mp4 (19.69 MB)
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Part 1 An introduction to machine learning engineering.mp4 (4.72 MB)
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Part 2 Preparing for production Creating maintainable ML.mp4 (3.96 MB)
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Part 3 Developing production machine learning code.mp4 (2.3 MB)
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