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Oreilly Machine Learning Engineering in Action - AD-TEAM - 06-04-2024
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mp4 | Video: h264,1280X720 | Audio: AAC, 44.1 KHz Genre:eLearning | Language: English | Size:2.33 GB Files Included : Appendix A Analyzing decision-tree complexity.mp4 (20.02 MB) MP4 Appendix A Big O(no) and how to think about runtime performance.mp4 (22.16 MB) MP4 Appendix A Complexity by example.mp4 (34.17 MB) MP4 Appendix A General algorithmic complexity for ML.mp4 (18.24 MB) MP4 Appendix B Containers to deal with dependency hell.mp4 (8.68 MB) MP4 Appendix B Setting up a development environment (1).mp4 (7.53 MB) MP4 Appendix B Setting up a development environment.mp4 (7.12 MB) MP4 Chapter 1 Summary.mp4 (2.05 MB) MP4 Chapter 1 The core tenets of ML engineering.mp4 (61.81 MB) MP4 Chapter 1 The goals of ML engineering.mp4 (6.48 MB) MP4 Chapter 1 What is a machine learning engineer.mp4 (24.84 MB) MP4 Chapter 10 1Naming, structure, and code architecture.mp4 (26.26 MB) MP4 Chapter 10 Blind to issues Eating exceptions and other bad practices.mp4 (21.27 MB) MP4 Chapter 10 Excessively nested logic.mp4 (31.57 MB) MP4 Chapter 10 Standards of coding and creating maintainable ML code.mp4 (12.07 MB) MP4 Chapter 10 Summary.mp4 (4.88 MB) MP4 Chapter 10 Tuple unpacking and maintainable alternatives.mp4 (14.22 MB) MP4 Chapter 10 Use of global mutable objects.mp4 (21.67 MB) MP4 Chapter 11 Leveraging AB testing for attribution calculations.mp4 (58.58 MB) MP4 Chapter 11 Model measurement and why it s so important.mp4 (52.83 MB) MP4 Chapter 11 Summary.mp4 (1.4 MB) MP4 Chapter 12 Holding on to your gains by watching for drift.mp4 (67.83 MB) MP4 Chapter 12 Responding to drift.mp4 (25.89 MB) MP4 Chapter 12 Summary.mp4 (1.27 MB) MP4 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) MP4 Chapter 13 ML development hubris.mp4 (54.84 MB) MP4 Chapter 13 Premature generalization, premature optimization, and other bad ways to show how smart you are.mp4 (50.71 MB) MP4 Chapter 13 Summary.mp4 (5 MB) MP4 Chapter 13 Technology-driven development vs solution-driven development.mp4 (12.83 MB) MP4 Chapter 13 Unintentional obfuscation Could you read this if you didn t write it.mp4 (74.92 MB) MP4 Chapter 14 Avoiding cargo cult ML behavior.mp4 (27.97 MB) MP4 Chapter 14 Keeping things as simple as possible.mp4 (20.94 MB) MP4 Chapter 14 Monitoring everything else in the model life cycle.mp4 (16.36 MB) MP4 Chapter 14 Monitoring your features.mp4 (21.64 MB) MP4 Chapter 14 Summary.mp4 (6.25 MB) MP4 Chapter 14 Writing production code.mp4 (72.11 MB) MP4 Chapter 14 Wireframing ML projects.mp4 (27.3 MB) MP4 Chapter 15 End user vs internal use testing.mp4 (29.31 MB) MP4 Chapter 15 Fallbacks and cold starts.mp4 (36.2 MB) MP4 Chapter 15 Model interpretability.mp4 (41.72 MB) MP4 Chapter 15 Quality and acceptance testing.mp4 (41.04 MB) MP4 Chapter 15 Summary.mp4 (4.2 MB) MP4 Chapter 16 Feature stores.mp4 (33.37 MB) MP4 Chapter 16 Prediction serving architecture.mp4 (79.68 MB) MP4 Chapter 16 Production infrastructure.mp4 (34.73 MB) MP4 Chapter 16 Summary.mp4 (2.5 MB) MP4 Chapter 2 Co-opting principles of Agile software engineering.mp4 (17.5 MB) MP4 Chapter 2 Summary.mp4 (3.36 MB) MP4 Chapter 2 The foundation of ML engineering.mp4 (3.94 MB) MP4 Chapter 2 Your data science could use some engineering.mp4 (10.83 MB) MP4 Chapter 2 A foundation of simplicity.mp4 (11.55 MB) MP4 Chapter 3 Before you model Planning and scoping a project.mp4 (110.62 MB) MP4 Chapter 3 Summary.mp4 (1.31 MB) MP4 Chapter 3 Experimental scoping Setting expectations and boundaries.mp4 (80.88 MB) MP4 Chapter 4 Before you model Communication and logistics of projects.mp4 (131.66 MB) MP4 Chapter 4 Don t waste our time Meeting with cross-functional teams.mp4 (52.7 MB) MP4 Chapter 4 Planning for business rules chaos.mp4 (19.9 MB) MP4 Chapter 4 Setting limits on your experimentation.mp4 (47.48 MB) MP4 Chapter 4 Summary.mp4 (4.47 MB) MP4 Chapter 4 Talking about results.mp4 (16.9 MB) MP4 Chapter 5 Experimentation in action Planning and researching an ML project.mp4 (73.23 MB) MP4 Chapter 5 Performing experimental prep work.mp4 (76.32 MB) MP4 Chapter 5 Summary.mp4 (1.73 MB) MP4 Chapter 6 Experimentation in action Testing and evaluating a project.mp4 (130.17 MB) MP4 Chapter 6 Summary.mp4 (1.35 MB) MP4 Chapter 6 Whittling down the possibilities.mp4 (34.89 MB) MP4 Chapter 7 Choosing the right tech for the platform and the team.mp4 (53.63 MB) MP4 Chapter 7 Experimentation in action Moving from prototype to MVP.mp4 (64.26 MB) MP4 Chapter 7 Summary.mp4 (1.69 MB) MP4 Chapter 8 Experimentation in action Finalizing an MVP with MLflow and runtime optimization.mp4 (46.1 MB) MP4 Chapter 8 Scalability and concurrency.mp4 (18.82 MB) MP4 Chapter 8 Summary.mp4 (1.64 MB) MP4 Chapter 9 Debugging walls of text.mp4 (10.81 MB) MP4 Chapter 9 Designing modular ML code.mp4 (15.41 MB) MP4 Chapter 9 Modularity for ML Writing testable and legible code.mp4 (47.85 MB) MP4 Chapter 9 Summary.mp4 (2.6 MB) MP4 Chapter 9 Using test-driven development for ML.mp4 (19.69 MB) MP4 Part 1 An introduction to machine learning engineering.mp4 (4.72 MB) MP4 Part 2 Preparing for production Creating maintainable ML.mp4 (3.96 MB) MP4 Part 3 Developing production machine learning code.mp4 (2.3 MB) MP4 [To see links please register or login] |