| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ~Get Your Files Here ! | |||
| 1 - The round | |||
| 1. Welcome and what this course is for.mp4 | 10.9 MB | ||
| 1. Welcome and what this course is for_en-US.srt | 3.4 KB | ||
| 2 - The eight-step skeleton | |||
| 3 - Data and labels | |||
| 10. 03-data-labels-03-label-fallacy.en.pdf | 42.8 KB | ||
| 10. The label fallacy when your label is another model's output.mp4 | 30.7 MB | ||
| 10. The label fallacy when your label is another model's output_en-US.srt | 9.1 KB | ||
| 4 - Retrieval | |||
| 11. 04-retrieval-01-candidate-generation.en.pdf | 56.9 KB | ||
| 11. Candidate generation two-tower, and the constraint that produced it.mp4 | 31.5 MB | ||
| 11. Candidate generation two-tower, and the constraint that produced it_en-US.srt | 8.7 KB | ||
| 12. 04-retrieval-02-ann-and-cold-start.en.pdf | 77.7 KB | ||
| 12. ANN indexes, the recall dial, and cold start.mp4 | 27.1 MB | ||
| 12. ANN indexes, the recall dial, and cold start_en-US.srt | 8.7 KB | ||
| 5 - Ranking | |||
| 13. 05-ranking-01-model-ladder.en.pdf | 63.8 KB | ||
| 13. The model ladder, from logistic regression to GBDT to GBDT plus LR to a deep mod.mp4 | 34.6 MB | ||
| 13. The model ladder, from logistic regression to GBDT to GBDT plus LR to a deep mod_en-US.srt | 9 KB | ||
| 14. 05-ranking-02-multitask-ranking.en.pdf | 66.8 KB | ||
| 14. Multi-task ranking, shared layers, per-engagement heads, and the combined loss.mp4 | 28.9 MB | ||
| 14. Multi-task ranking, shared layers, per-engagement heads, and the combined loss_en-US.srt | 8.9 KB | ||
| 15. 05-ranking-03-crosses-and-calibration.en.pdf | 64.6 KB | ||
| 15. Feature crosses, DCN, and calibration, or why area under the curve can look fine.mp4 | 36.4 MB | ||
| 15. Feature crosses, DCN, and calibration, or why area under the curve can look fine_en-US.srt | 9.1 KB | ||
| 6 - Serving and monitoring | |||
| 16. 06-serving-01-batch-online-hybrid.en.pdf | 54.3 KB | ||
| 16. Batch, online, and hybrid inference, and the feature store underneath.mp4 | 29 MB | ||
| 16. Batch, online, and hybrid inference, and the feature store underneath_en-US.srt | 8.4 KB | ||
| 17. 06-serving-02-offline-online-gap.en.pdf | 50.1 KB | ||
| 17. The diagnosis ladder excellent offline, flat in production.mp4 | 31.7 MB | ||
| 17. The diagnosis ladder excellent offline, flat in production_en-US.srt | 9.1 KB | ||
| 18. 06-serving-03-continual-training.en.pdf | 64.4 KB | ||
| 18. Continual training, cadence, and the freshness argument.mp4 | 37.1 MB | ||
| 18. Continual training, cadence, and the freshness argument_en-US.srt | 8.8 KB | ||
| 7 - Metrics | |||
| 19. 07-metrics-01-offline-metrics.en.pdf | 67.6 KB | ||
| 19. Offline metrics choosing from what the score is used for.mp4 | 32.9 MB | ||
| 19. Offline metrics choosing from what the score is used for_en-US.srt | 8.6 KB | ||
| 20. 07-metrics-02-online-metrics-guardrails.en.pdf | 69.4 KB | ||
| 20. The online readout primary metric, guardrails, and the domain metrics.mp4 | 39.1 MB | ||
| 20. The online readout primary metric, guardrails, and the domain metrics_en-US.srt | 9 KB | ||
| 8 - The cases | |||
| 21. 08-cases-01-news-feed.en.pdf | 80.8 KB | ||
| 21. Personalized news feed the full forty-five minutes.mp4 | 59.9 MB | ||
| 21. Personalized news feed the full forty-five minutes_en-US.srt | 12.1 KB | ||
| 22. 08-cases-02-ads-click-prediction.en.pdf | 74.3 KB | ||
| 22. Ads click prediction the full design, and the four follow-ups that decide it.mp4 | 48.7 MB | ||
| 22. Ads click prediction the full design, and the four follow-ups that decide it_en-US.srt | 11.9 KB | ||
| 23. 08-cases-03-harmful-content.en.pdf | 79.9 KB | ||
| 23. Harmful content detection designing when the labels do not exist yet.mp4 | 45.3 MB | ||
| 23. Harmful content detection designing when the labels do not exist yet_en-US.srt | 12.1 KB | ||
| 24. 08-cases-04-the-catalog.en.pdf | 43.8 KB | ||
| 24. The catalog map any prompt to its nearest solved family.mp4 | 36.5 MB | ||
| 24. The catalog map any prompt to its nearest solved family_en-US.srt | 8.8 KB | ||
| 25. 08-cases-05-timed-mocks.en.pdf | 66.2 KB | ||
| 25. Two timed mocks and the scoring rubric.mp4 | 39.9 MB | ||
| 25. Two timed mocks and the scoring rubric_en-US.srt | 10.1 KB | ||
| 25. c4-next-steps.en.pdf | 30.8 KB | ||
| 8. 03-data-labels-01-where-labels-come-from.en.pdf | 39.9 KB | ||
| 8. Where labels come from implicit, explicit, and negative engagement.mp4 | 24.5 MB | ||
| 8. Where labels come from implicit, explicit, and negative engagement_en-US.srt | 8.7 KB | ||
| 9. 03-data-labels-02-negative-sampling.en.pdf | 48.9 KB | ||
| 9. Negative sampling exposure bias, position bias, dedupe, and the ratio.mp4 | 28.3 MB | ||
| 9. Negative sampling exposure bias, position bias, dedupe, and the ratio_en-US.srt | 8.7 KB | ||
| 5. 02-the-skeleton-01-eight-steps.en.pdf | 47.9 KB | ||
| 5. The 8-step spine, and the second layer beneath every step.mp4 | 28.4 MB | ||
| 5. The 8-step spine, and the second layer beneath every step_en-US.srt | 8.3 KB | ||
| 6. 02-the-skeleton-02-differentiator-doctrine.en.pdf | 47.7 KB | ||
| 6. The differentiator doctrine open by naming what makes this system different.mp4 | 27.3 MB | ||
| 6. The differentiator doctrine open by naming what makes this system different_en-US.srt | 8.3 KB | ||
| 7. 02-the-skeleton-03-worked-pass.en.pdf | 44.7 KB | ||
| 7. Worked pass the whole spine in ten minutes, on a prompt you have not seen.mp4 | 25.3 MB | ||
| 7. Worked pass the whole spine in ten minutes, on a prompt you have not seen_en-US.srt | 8.1 KB | ||
| 2. 01-the-round-01-format-and-scoring.en.pdf | 38.6 KB | ||
| 2. The round variants, who asks it, and what the scorecard says.mp4 | 23.8 MB | ||
| 2. The round variants, who asks it, and what the scorecard says_en-US.srt | 8.2 KB | ||
| 3. 01-the-round-02-time-budget.en.pdf | 40.5 KB | ||
| 3. The time budget the senior allocation, live self-monitoring, and recovery.mp4 | 20.2 MB | ||
| 3. The time budget the senior allocation, live self-monitoring, and recovery_en-US.srt | 7.1 KB | ||
| 4. 01-the-round-03-clarifying-questions.en.pdf | 43.1 KB | ||
| 4. Clarifying questions the first scored answer.mp4 | 23.2 MB | ||
| 4. Clarifying questions the first scored answer_en-US.srt | 8.1 KB |
The ML System Design Interview: Depth, Not Templates
https://WebToolTip.com
Published 8/2026
Created by OfferLab Courses
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Expert | Genre: eLearning | Language: English + subtitle | Duration: 25 Lectures ( 2h 27m ) | Size: 803.2 MB
Interviewers can hear a template. Learn the eight-step spine, then the judgment that sits on top of it.
What you'll learn
⚡ Allocate 45 minutes so no stage starves, and self-monitor the clock while you are talking
⚡ Turn a one-line prompt into a scoped problem using clarifying questions that already score points
⚡ Run the eight-step spine on any prompt: clarify, goal, data and labels, features, retrieval, ranking, serving, metrics
⚡ Open any design by naming what makes this system different from a generic recommender
⚡ Derive labels from product events, and detect when a proposed label is really another model's output
⚡ Design retrieval for a hundred million items under a latency budget, and explain cold start
⚡ Justify each rung of the ranking ladder, and say why AUC can flatter a model that is miscalibrated
⚡ Answer "how did you deploy it" without freezing, and run two timed mocks scored against a senior rubric
Requirements
❗ Working knowledge of classical ML (you can explain a gradient-boosted tree and a train/validation split)
❗ Some professional or project experience building models. This is not a first ML course
❗ No coding is required during the round, and none is required here
| torrent name | size | uploader | age | seed | leech |
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| 527.5 MB | freecoursewb | 1 day | 1 | 12 | |
| 784.3 MB | freecoursewb | 2 weeks | 18 | 6 | |
| 2.2 GB | freecoursewb | 2 weeks | 18 | 7 | |
| 3.7 GB | freecoursewb | 2 weeks | 17 | 3 | |
| 3.3 GB | freecoursewb | 2 weeks | 20 | 2 |
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