![Hero of the day
Szilard [Deeper than Deep
Learning] @DataScienceLA
-=-
Be#er than Deep Learning:
Gradient Boos4ng Machines
(GBMs)
https://github.com/
szilard/benchm-ml](https://image.slidesharecdn.com/danielmolnarthedatajanitorreturnsdatanatives-200123123849/85/The-Data-Janitor-Returns-Daniel-Molnar-DN18-30-320.jpg)
![Spark MLlibs GBM implementa3on is 10x
slower, uses 10x more memory and is buggy/
lower accuracy. Total fucking garbage!
— Szilard [Deeper than Deep Learning] @DataScienceLA](https://image.slidesharecdn.com/danielmolnarthedatajanitorreturnsdatanatives-200123123849/85/The-Data-Janitor-Returns-Daniel-Molnar-DN18-31-320.jpg)
The Data Janitor Returns | Daniel Molnar | DN18
- 1. Daniel Molnar @ Oberlo/Shopify / Data Natives @ Berlin @ 2018-11-22
- 2. Where I'm coming from • senior data analy.cs engineer, • head of data and analy.cs, • senior applied and data scien.st, • data analyst, • or just data janitor.
- 3. Perspec've • rounded, not complete, • slow, old, stupid and lazy and
- 4. tl;dr (new) • KISS is the philosophy, • take the long view, invest in durable knowledge, • strive for fast and good enough, • just because you can doesn't mean you should, • figure what to worry about, • you are not Google.
- 5. it used to be a hype now this is a war nobody's your friend they want your money and data (preferably both locked in)
- 6. Things you worry about: • machine learning, • deep learning, • GDPR.
- 7. Things you should really worry about: • machine learning adblockers, • deep learning ELT, • GDPR, CRM (yes, CRM).
- 12. Look at the *** data
- 14. Usual suspect: NPS • one, simple number you can squint at, • sampling is skewed, • answer is unsure, • easy to hack step func:on1 , MONKEYPATCH: look at the change of the distro. 1 Eve Rajca aka @EveTheAnalyst and Jacques Ma9heij aka @jma9heij
- 15. Google Analy&cs?
- 16. Hero of the day Mar$n Loetzsch @mar$n_loetzsch -=- KPIs for e-commerce startups Data Science in Early Stage Startups: the Struggle to Create Value https://github.com/mara
- 18. LEARN & OPTIMIZE
- 19. Half of the *me when companies say they need "AI" what they really need is a SELECT clause with GROUP BY. You're welcome. — Mat Velloso @matvelloso (Technical Advisor to CTO at Microso9)
- 20. Don't do A/B tests 99% it will not worth doing it
- 21. ... conversion rate is 2% ... detec0ng a rela0ve change of 1% requires an experiment with 12 million users ... — Simon Jackson (Booking.com)
- 22. R?Shiny.
- 23. Usual suspects • Non-reproducable experiments and tests. • R hodpepodge in produc9on. • Beliefs hidden as implicits in models.
- 25. ML~AI~DEEP*
- 26. You don't have (enough) data.
- 27. Make your own data points!
- 28. Deploy good enough fast?
- 29. Deep learn my *** Do you really need it? Tensorflow! ... ... so distributed deep learning can compress porn on the end device.
- 30. Hero of the day Szilard [Deeper than Deep Learning] @DataScienceLA -=- Be#er than Deep Learning: Gradient Boos4ng Machines (GBMs) https://github.com/ szilard/benchm-ml
- 31. Spark MLlibs GBM implementa3on is 10x slower, uses 10x more memory and is buggy/ lower accuracy. Total fucking garbage! — Szilard [Deeper than Deep Learning] @DataScienceLA
- 35. Q: Why are there so many programmers from Eastern Europe? A: Slavic pessimism. Everything that can go wrong will go wrong. With such a mindset programming comes naturally. — Mar&n Sustrik @sustrik (Creator of ZeroMQ, nanomsg, libdill.)
- 37. over engineering
- 38. you get an other machine if you can use one
- 40. Get cloud agnos.c! • AWS s'll leads the pack by far • Azure will sell anyway, and all will cry, • Google competes with the cheap and uncooked
- 41. ETL is #solved OMG • Airflow is an overengineered underperforming nightmare, • metl for source mappings in magnitude, • Mara for generic e-commerce, • night-shift for explicit minimalism.
- 42. Showdown
- 43. Hero of the day Mark Litwintschik @marklit82 Summary of the 1.1 Billion Taxi Rides Benchmarks (500 GB uncompressed CSV) https:// tech.marksblogg.com
- 44. Spark Setup Query Median QM per vCPU Cost/hour 11 x m3.xlarge + HDFS 14,91 0,34 27,5 1 x i3.8xlarge + HDFS 26,00 0,81 2,5 21 x m3.xlarge + HDFS 32,00 0,38 5,67 5 x m3.xlarge + S3 466,50 23,33 1,35 3 x Raspberry Pi 1738,00 144,83 HDFS. RPi = 1/6 VCPU ~100 EUR. Linear scaling.
- 45. Presto Setup Query Median QM per vCPU Cost/hour 50 x n1-standard-4 7,00 0,04 9.50 21 x m3.xlarge 11,50 0,14 5.67 10 x n1-standard-4 16,00 0,36 2.09 1 x i3.8xlarge + HDFS 15,00 0,47 2.50 5 x m3.xlarge + HDFS 51,50 0,26 1.35 50 x m3.xlarge + S3 43,50 0,22 13.50 Workhorse in favour. HDFS. 1 machine. Non-linear scaling.
- 46. Lazy Evalua*on Setup Query Median Cost/hour Redshi', 6 x ds2.8xlarge 1,91 40.80 BigQuery 2,00 Amazon Athena 6,30 Presto, 50 x n1-standard-4 7,00 9.50 Spark, 11 x m3.xlarge + HDFS 14,91 27.50 The human cost -- in both terms.
- 47. One Machine Setup Query Median QM per vCPU Cost/hour ClickHouse 4,21 1,05 Elas3csearch tuned 13,14 3,29 Presto, 1 x i3.8xlarge + HDFS 15,00 0.47 2.50 Spark, 1 x i3.8xlarge + HDFS 26,00 0,81 2.50 Ver3ca 32,80 8,20 Elas3csearch 48,89 12,22 PSQL 9.5 + cstore_fdw 205,00 51,25 Intel Core i5 4670K VS i3.8xlarge (32 VCPUs). Desktop example costs <600 EUR.
- 49. Do you use Google Analy+cs?
- 50. 9%of the events are lost to ~all third party trackers due to adblocking.
- 51. Sink > Sieve > Sort ELT aka SQL on flat files with the minimum amount of code wri:en.
- 53. BIRD OF PREY
- 54. Who are you? • Lip service provider. • Fake news producer. • Kingmaker. Are you the fool or the grey eminent?
- 55. Don't believe the hype. HR: good people leave.
- 56. Marke&ng
- 57. Will this ever get be-er? • adblocking, • CPA silver bullets are gone, • conversion & a8ribu9on are hard nuts, • FB and GO are not your friends (the 900% on videos), • but CRM is.
- 58. GDPR • road to hell is paved with good inten2ons, • it's about the process, matey, • mostly fair, • yes, you have to clean up your mess, • dunno, wouldn't buy programma2c shares1 . 1 Eve Rajca aka @EveTheAnalyst and Jacques Ma9heij aka @jma9heij
- 59. Thank you! @soobrosa We're hiring! visuals: @mroga., @xkcd, @DorsaAmir, ˙Cаvin 〄, thelearningcurvedotca, JD Hancock, Thomas Hawk, jonolist, Kalexanderson, Shopify Burst