Lock in $30 Savings on PRO—Offer Ends Soon! ⏳
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
A Random Walk in Data Science and Machine Learn...
Search
szilard
February 12, 2020
0
290
A Random Walk in Data Science and Machine Learning in Practice - CEU, Business Analytics Masters - Budapest, Febr 2020
szilard
February 12, 2020
Tweet
Share
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
140
Make Machine Learning Boring Again: Best Practices for Using Machine Learning in Businesses - Albuquerque Machine Learning Meetup (Online) - Aug 2020
szilard
0
96
Better than Deep Learning: Gradient Boosting Machines (GBM) - eRum conference - invited talk - June 2020
szilard
0
92
Gradient Boosting Machines (GBM): From Zero to Hero (with R and Python Code) - LA Data Science Meetup - February 2020
szilard
0
84
Better than My Meetup/Conference Talks: Going Deeper in Various GBM Topics - GBM Advanced Workshop - Budapest, Nov 2019
szilard
0
54
Gradient Boosting Machines (GBM): From Zero to Hero (with R and Python Code) - Budapest BI Forum, Budapest, Nov 2019
szilard
0
130
Make Machine Learning Boring Again: Best Practices for Using Machine Learning in Businesses - LA Data Science Meetup - Playa Vista, August 2019
szilard
0
100
Better than Deep Learning: Gradient Boosting Machines (GBM) / 2019 edition - Budapest R and Data Science Meetups - Budapest, June 2019
szilard
0
80
Better than Deep Learning: Gradient Boosting Machines (GBM) / 2019 edition - LA R Meetup - Santa Monica, May 2019
szilard
0
20
Featured
See All Featured
The Art of Delivering Value - GDevCon NA Keynote
reverentgeek
8
1.2k
Site-Speed That Sticks
csswizardry
1
130
Designing for Performance
lara
604
68k
Typedesign – Prime Four
hannesfritz
40
2.4k
Testing 201, or: Great Expectations
jmmastey
40
7.1k
The Art of Programming - Codeland 2020
erikaheidi
53
13k
The Cost Of JavaScript in 2023
addyosmani
45
6.9k
Product Roadmaps are Hard
iamctodd
PRO
49
11k
The Cult of Friendly URLs
andyhume
78
6.1k
RailsConf & Balkan Ruby 2019: The Past, Present, and Future of Rails at GitHub
eileencodes
132
33k
How to train your dragon (web standard)
notwaldorf
88
5.7k
The MySQL Ecosystem @ GitHub 2015
samlambert
250
12k
Transcript
A Random Walk in Data Science and Machine Learning in
Practice Szilard Pafka, PhD Chief Scientist, Epoch (USA) CEU, Business Analytics Masters Budapest, Febr 2020
None
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
None
None
CRISP-DM, 1999
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
Better than Deep Learning: Gradient Boosting Machines (GBM) - 2019
Updated Edition Szilard Pafka, PhD Chief Scientist, Epoch (USA) Barcelona, Los Angeles, Budapest, Berlin (confs/meetups) 2019
None
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
Source: Andrew Ng
Source: Andrew Ng
Source: Andrew Ng
None
None
None
None
Source: https://twitter.com/iamdevloper/
None
None
...
None
None
None
http://lowrank.net/nikos/pubs/empirical.pdf http://www.cs.cornell.edu/~alexn/papers/empirical.icml06.pdf
http://lowrank.net/nikos/pubs/empirical.pdf http://www.cs.cornell.edu/~alexn/papers/empirical.icml06.pdf
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
Source: Hastie etal, ESL 2ed
Source: Hastie etal, ESL 2ed
Source: Hastie etal, ESL 2ed
Source: Hastie etal, ESL 2ed
None
None
None
None
None
None
10x
None
None
None
10x
10x
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
http://www.jmlr.org/papers/volume13/bergstra12a/bergstra12a.pdf
http://www.argmin.net/2016/06/20/hypertuning/
None
None
None
None
None
None
None
CPU 1
CPU 1 CPU 2
CPU 1 CPU 2
CPU 1 CPU 2
CPU 1 CPU 2
None
None
None
None
None
None
None
*
None
no-one is using this crap
(2018)
(2018)
None
Source: https://www.linkedin.com/pulse/winning-solution-kaggledays-2019-competition-san-francisco-mark-peng/
Source: https://www.linkedin.com/pulse/winning-solution-kaggledays-2019-competition-san-francisco-mark-peng/
Source: https://www.linkedin.com/pulse/winning-solution-kaggledays-2019-competition-san-francisco-mark-peng/
Source: https://www.linkedin.com/pulse/winning-solution-kaggledays-2019-competition-san-francisco-mark-peng/
Source: https://www.linkedin.com/pulse/winning-solution-kaggledays-2019-competition-san-francisco-mark-peng/
Source: https://www.linkedin.com/pulse/winning-solution-kaggledays-2019-competition-san-francisco-mark-peng/
None
More:
None
A Few More Thoughts
None
None
None
None
None
None
None
None
None
None
None
None
None