Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
Machine Learning Trends in 2017 - Budapest Data...
Search
szilard
December 19, 2017
0
120
Machine Learning Trends in 2017 - Budapest Data Christmas - Dec 2017
szilard
December 19, 2017
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
190
Make Machine Learning Boring Again: Best Practices for Using Machine Learning in Businesses - Albuquerque Machine Learning Meetup (Online) - Aug 2020
szilard
0
140
Better than Deep Learning: Gradient Boosting Machines (GBM) - eRum conference - invited talk - June 2020
szilard
0
130
Gradient Boosting Machines (GBM): From Zero to Hero (with R and Python Code) - LA Data Science Meetup - February 2020
szilard
0
120
A Random Walk in Data Science and Machine Learning in Practice - CEU, Business Analytics Masters - Budapest, Febr 2020
szilard
0
300
Better than My Meetup/Conference Talks: Going Deeper in Various GBM Topics - GBM Advanced Workshop - Budapest, Nov 2019
szilard
0
82
Gradient Boosting Machines (GBM): From Zero to Hero (with R and Python Code) - Budapest BI Forum, Budapest, Nov 2019
szilard
0
150
Make Machine Learning Boring Again: Best Practices for Using Machine Learning in Businesses - LA Data Science Meetup - Playa Vista, August 2019
szilard
0
130
Better than Deep Learning: Gradient Boosting Machines (GBM) / 2019 edition - Budapest R and Data Science Meetups - Budapest, June 2019
szilard
0
97
Featured
See All Featured
Optimising Largest Contentful Paint
csswizardry
37
3.5k
How to Ace a Technical Interview
jacobian
280
24k
Learning to Love Humans: Emotional Interface Design
aarron
274
41k
The Success of Rails: Ensuring Growth for the Next 100 Years
eileencodes
46
7.8k
Bootstrapping a Software Product
garrettdimon
PRO
307
110k
Refactoring Trust on Your Teams (GOTO; Chicago 2020)
rmw
35
3.2k
Dealing with People You Can't Stand - Big Design 2015
cassininazir
367
27k
No one is an island. Learnings from fostering a developers community.
thoeni
21
3.5k
"I'm Feeling Lucky" - Building Great Search Experiences for Today's Users (#IAC19)
danielanewman
231
22k
Code Reviewing Like a Champion
maltzj
527
40k
Java REST API Framework Comparison - PWX 2021
mraible
34
9k
Chrome DevTools: State of the Union 2024 - Debugging React & Beyond
addyosmani
9
980
Transcript
Machine Learning Trends in 2017 Szilárd Pafka, PhD Chief Scientist,
Epoch Budapest Data Christmas December 2017
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
Source: Andrew Ng
None
None
None
None
...
None
None
None
None
None
None
None
None
None
10x
10x
None
None
None
None
None
None
None
1M: CPU cache effects
(lightgbm 10M)
16 cores vs 1: 16 cores:
None
None
Aggregation 100M rows 1M groups Join 100M rows x 1M
rows time [s] time [s]
Aggregation 100M rows 1M groups Join 100M rows x 1M
rows time [s] time [s]
None
None
None
None
None
me @confs / talks :: 2017