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Oreilly Managing Machine Learning Projects Video Edition FreeCourseWeb

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Added Monday 1st January 2024 05:41:20 PM (2 years ago)
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Torrent Files (74)
FilenameSize
Get Bonus Downloads Here.url183 bytes
001. Chapter 1. Introduction Delivering machine learning projects is hard; let’s do it better.mp418.9 MB
002. Chapter 1. Why is ML important.mp413.6 MB
003. Chapter 1. Other machine learning methodologies.mp413.7 MB
004. Chapter 1. Understanding this book.mp46.3 MB
005. Chapter 1. Case study The Bike Shop.mp42.7 MB
006. Chapter 1. Summary.mp41.9 MB
007. Chapter 2. Pre-project From opportunity to requirements.mp417.9 MB
008. Chapter 2. Project management infrastructure.mp46.2 MB
009. Chapter 2. Project requirements.mp427.6 MB
010. Chapter 2. Data.mp417.3 MB
011. Chapter 2. Security and privacy.mp44.9 MB
012. Chapter 2. Corporate responsibility, regulation, and ethical considerations.mp420.2 MB
013. Chapter 2. Development architecture and process.mp414.3 MB
014. Chapter 2. Summary.mp42.2 MB
015. Chapter 3. Pre-project From requirements to proposal.mp417.6 MB
016. Chapter 3. Create an estimate.mp449.4 MB
017. Chapter 3. Pre-salespre-project administration.mp43.4 MB
018. Chapter 3. Pre-projectpre-sales checklist.mp46.2 MB
019. Chapter 3. The Bike Shop pre-sales.mp428.8 MB
020. Chapter 3. Pre-project postscript.mp45.0 MB
021. Chapter 3. Summary.mp41.5 MB
022. Chapter 4. Getting started.mp44.7 MB
023. Chapter 4. Finalize team design and resourcing.mp43.6 MB
025. Chapter 4. Infrastructure plan.mp49.0 MB
026. Chapter 4. The data story.mp425.9 MB
027. Chapter 4. Privacy, security, and an ethics plan.mp43.8 MB
028. Chapter 4. Project roadmap.mp46.2 MB
029. Chapter 4. Sprint 0 checklist.mp42.5 MB
030. Chapter 4. Bike Shop project setup.mp430.4 MB
031. Chapter 4. Summary.mp42.1 MB
032. Chapter 5. Diving into the problem.mp44.3 MB
033. Chapter 5. Understanding the data.mp439.6 MB
034. Chapter 5. Business problem refinement, UX, and application design.mp424.7 MB
035. Chapter 5. Building data pipelines.mp444.8 MB
036. Chapter 5. Model repository and model versioning.mp417.9 MB
037. Chapter 5. Summary.mp42.5 MB
038. Chapter 6. EDA, ethics, and baseline evaluations.mp458.5 MB
039. Chapter 6. Ethics checkpoint.mp47.9 MB
040. Chapter 6. Baseline models and performance.mp43.5 MB
041. Chapter 6. What if there are problems.mp47.7 MB
042. Chapter 6. Pre-modeling checklist.mp4843.8 KB
043. Chapter 6. The Bike Shop Pre-modelling.mp447.3 MB
045. Chapter 7. Making useful models with ML.mp410.0 MB
046. Chapter 7. Feature engineering and data augmentation.mp430.5 MB
048. Chapter 7. Making models with ML.mp427.3 MB
049. Chapter 7. Stinky, dirty, no good, smelly models.mp46.7 MB
050. Chapter 7. Summary.mp42.5 MB
051. Chapter 8. Testing and selection.mp49.2 MB
052. Chapter 8. Testing processes.mp469.9 MB
053. Chapter 8. Model selection.mp426.0 MB
054. Chapter 8. Post modelling checklist.mp44.3 MB
055. Chapter 8. The Bike Shop sprint 2.mp437.1 MB
056. Chapter 8. Summary.mp44.1 MB
057. Chapter 9. Sprint 3 system building and production.mp410.3 MB
058. Chapter 9. Types of ML implementations.mp431.2 MB
059. Chapter 9. Nonfunctional review.mp45.7 MB
060. Chapter 9. Implementing the production system.mp457.0 MB
061. Chapter 9. Logging, monitoring, management, feedback, and documentation.mp421.5 MB
062. Chapter 9. Pre-release testing.mp45.4 MB
063. Chapter 9. Ethics review.mp43.4 MB
064. Chapter 9. Promotion to production.mp44.9 MB
065. Chapter 9. You aren’t done yet.mp42.1 MB
066. Chapter 9. The Bike Shop sprint 3.mp415.9 MB
067. Chapter 9. Summary.mp44.2 MB
068. Chapter 10. Post project (sprint Ω).mp41.8 MB
069. Chapter 10. Off your hands and into production.mp430.7 MB
070. Chapter 10. Team post-project review.mp48.4 MB
071. Chapter 10. Improving practice.mp46.9 MB
072. Chapter 10. New technology adoption.mp43.2 MB
073. Chapter 10. Case study.mp41.9 MB
074. Chapter 10. Goodbye and good luck.mp42.3 MB
075. Chapter 10. Summary.mp42.7 MB
Bonus Resources.txt386 bytes
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