Upgrade to Pro — share decks privately, control downloads, hide ads and more …

Better than Deep Learning: Gradient Boosting M...

szilard
June 17, 2020
Technology
0
100

Better than Deep Learning: Gradient Boosting Machines (GBM) - eRum conference - invited talk - June 2020

szilard

June 17, 2020
Tweet

More Decks by szilard

See All by szilard
Gradient Boosting Machines (GBM): From Zero to Hero (with R and Python Code) - Data Con LA - Oct 2020
szilard
0
160
Make Machine Learning Boring Again: Best Practices for Using Machine Learning in Businesses - Albuquerque Machine Learning Meetup (Online) - Aug 2020
szilard
0
110
Gradient Boosting Machines (GBM): From Zero to Hero (with R and Python Code) - LA Data Science Meetup - February 2020
szilard
0
97
A Random Walk in Data Science and Machine Learning in Practice - CEU, Business Analytics Masters - Budapest, Febr 2020
szilard
0
290
Better than My Meetup/Conference Talks: Going Deeper in Various GBM Topics - GBM Advanced Workshop - Budapest, Nov 2019
szilard
0
62
Gradient Boosting Machines (GBM): From Zero to Hero (with R and Python Code) - Budapest BI Forum, Budapest, Nov 2019
szilard
0
140
Make Machine Learning Boring Again: Best Practices for Using Machine Learning in Businesses - LA Data Science Meetup - Playa Vista, August 2019
szilard
0
110
Better than Deep Learning: Gradient Boosting Machines (GBM) / 2019 edition - Budapest R and Data Science Meetups - Budapest, June 2019
szilard
0
86
Better than Deep Learning: Gradient Boosting Machines (GBM) / 2019 edition - LA R Meetup - Santa Monica, May 2019
szilard
0
22

Other Decks in Technology

See All in Technology
TopAppBar Composableをカスタムする
hunachi
0
170
AI Agentを「期待通り」に動かすために：設計アプローチの模索と現在地
kworkdev
PRO
1
170
Enterprise AI in 2025?
pamelafox
0
150
Webアプリを Lambdaで動かすまでに考えること / How to implement monolithic Lambda Web Application
_kensh
7
1.1k
改めて学ぶ Trait の使い方 / phpcon odawara 2025
meihei3
1
420
アセスメントで紐解く、10Xのデータマネジメントの軌跡
10xinc
1
210
Spice up your notifications/try!Swift25
noppefoxwolf
2
160
OPENLOGI Company Profile
hr01
0
62k
古き良き Laravel のシステムは関数型スタイルでリファクタできるのか
leveragestech
1
600
OSSコントリビュートをphp-srcメンテナの立場から語る / OSS Contribute
sakitakamachi
0
1.1k
Lightdashの利活用状況 ー導入から2年経った現在地_20250409
hirokiigeta
2
260
Tirez profit de Messenger pour améliorer votre architecture
tucksaun
1
220

Featured

See All Featured
Stop Working from a Prison Cell
hatefulcrawdad
268
20k
GraphQLの誤解/rethinking-graphql
sonatard
70
10k
Why You Should Never Use an ORM
jnunemaker
PRO
55
9.3k
Keith and Marios Guide to Fast Websites
keithpitt
411
22k
Put a Button on it: Removing Barriers to Going Fast.
kastner
60
3.8k
How to Create Impact in a Changing Tech Landscape [PerfNow 2023]
tammyeverts
51
2.4k
Distributed Sagas: A Protocol for Coordinating Microservices
caitiem20
331
21k
Build The Right Thing And Hit Your Dates
maggiecrowley
35
2.6k
Fontdeck: Realign not Redesign
paulrobertlloyd
83
5.5k
Automating Front-end Workflow
addyosmani
1369
200k
Fight the Zombie Pattern Library - RWD Summit 2016
marcelosomers
233
17k
VelocityConf: Rendering Performance Case Studies
addyosmani
328
24k

Transcript

  1. Better than Deep Learning: Gradient Boosting Machines (GBM) Szilard Pafka,

    PhD Chief Scientist, Epoch (USA) e-Rum conference, Milano, Italy / Online June 2020
  2. None

  3. Disclaimer: I am not representing my employer (Epoch) in this

    talk I cannot confirm nor deny if Epoch is using any of the methods, tools, results etc. mentioned in this talk

  4. Source: Andrew Ng

  5. Source: Andrew Ng

  6. Source: Andrew Ng

  7. None
  8. None
  9. None
  10. None

  11. Source: https://twitter.com/iamdevloper/

  12. None
  13. None

  14. ...

  15. None
  16. None
  17. None

  18. http://lowrank.net/nikos/pubs/empirical.pdf http://www.cs.cornell.edu/~alexn/papers/empirical.icml06.pdf

  19. http://lowrank.net/nikos/pubs/empirical.pdf http://www.cs.cornell.edu/~alexn/papers/empirical.icml06.pdf

  20. None
  21. None
  22. None
  23. None
  24. None
  25. None
  26. None
  27. None
  28. None
  29. None
  30. None

  31. Source: Hastie etal, ESL 2ed

  32. Source: Hastie etal, ESL 2ed

  33. None
  34. None

  35. 10x

  36. None
  37. None

  38. 10x

  39. 10x

  40. None
  41. None
  42. None
  43. None
  44. None
  45. None
  46. None
  47. None
  48. None
  49. None
  50. None
  51. None
  52. None
  53. None
  54. None
  55. None
  56. None
  57. None
  58. None
  59. None
  60. None
  61. None
  62. None

  63. Source: https://www.linkedin.com/pulse/winning-solution-kaggledays-2019-competition-san-francisco-mark-peng/

  64. Source: https://www.linkedin.com/pulse/winning-solution-kaggledays-2019-competition-san-francisco-mark-peng/

  65. Source: https://www.linkedin.com/pulse/winning-solution-kaggledays-2019-competition-san-francisco-mark-peng/

  66. Source: https://www.linkedin.com/pulse/winning-solution-kaggledays-2019-competition-san-francisco-mark-peng/

  67. Source: https://www.linkedin.com/pulse/winning-solution-kaggledays-2019-competition-san-francisco-mark-peng/

  68. Source: https://www.linkedin.com/pulse/winning-solution-kaggledays-2019-competition-san-francisco-mark-peng/

  69. None

  70. More:

  71. More:

  72. More:

  73. None