veyepar: The Developer's Guide to Data Science

Author(s):	Helge Reikeras
Location	Cedarwood
Date	oct Thu 11	Days Raw Files
Start	11:35	First Raw Start	11:17
Duration	00:45:00	Offset	0:17:53
End	12:20	Last Raw End	12:47
Chapters	00:00 0:08:15 0:32:01 0:38:14
Total cuts_time	39 min.

https://za.pycon.org/talks/30-the-developers-guide-to-data-science/
raw-playlist raw-mp4-playlist encoded-files-playlist host archive tweet mp4 svg png

assets release.pdf The_Developers_Guide_to_Data_Science.json
logs
Admin: episode episode list cut list raw files day marks day marks day image_files

State:

Locked:

clear this to unlock

Locked by:

user/process that locked.

Start:

initially scheduled time from master, adjusted to match reality

Duration:

length in hh:mm:ss

Name:

Video Title (shows in video search results)

Emails:

email(s) of the presenter(s)

Released:

has someone authorised pubication

Normalise:

Channelcopy:

m=mono, 01=copy left to right, 10=right to left, 00=ignore.

Thumbnail:

filename.png

Description:

markdown

The myth of data science holds that you need an army of machine learning PHDs to be able to implement anything impactful with data science. In this talk I will attempt to dispel this myth and show how software developers can skip getting the machine learning PHD and start building awesome software with Data Science and Machine Learning today.

I believe developers are well situated to implement data science projects as they possess the understanding of how the product works, how users like to interact with the product and their opinions are already valued within the business.

To help developers level up their data science skills, I’ll discuss the core concepts behind the most prevalent methods in data science, how the data science process works, how to think like a data scientist, which frameworks and programming languages to choose (surprise Python!) and how to measure and communicate the value-add of data science projects to the business.

<em>About the speaker: Helge Reikeras is a Data Scientist at Offerzen with over 6 years experience in practical data science and has also worked as a software developer at various points in his career.
</em>

Comment:

production notes

2018-10-11/11_17_07.ts Apply: 11:38:50 - 11:47:06 ( 00:08:15 ) S: 11:17:07 - E: 11:47:06 D: 00:29:59 (Start: 1303.490123) show more...

vlc ~/Videos/veyepar/pyconza/pyconza2018/dv/cedarwood/2018-10-11/11_17_07.ts :start-time=01303.490123 --audio-desync=0

	Raw File	Cut List
	11:17:07		seconds: 1303.490123 Wall: 11:38:50
Duration	00:29:59
	11:47:06		seconds: 0.0 Wall: 11:17:07
Comments:
mp4 mp4.m3u	dv.m3u	Split: Sequence:: delete

2018-10-11/12_17_07.ts Apply: 12:18:51 - 12:22:19 ( 00:03:28 ) S: 12:17:07 - E: 12:47:07 D: 00:30:00 (Start: 104.0) (End: 312.0) show more...

vlc ~/Videos/veyepar/pyconza/pyconza2018/dv/cedarwood/2018-10-11/12_17_07.ts :start-time=0104.0 --audio-desync=0

	Raw File	Cut List
	12:17:07		seconds: 104.0 Wall: 12:18:51
Duration	00:30:00
	12:47:07		seconds: 312.0 Wall: 12:22:19
Comments:
mp4 mp4.m3u	dv.m3u	Split: Sequence:: delete

2018-10-11/12_17_07.ts Apply: 12:22:19 - 12:39:53 ( 00:17:34 ) S: 12:17:07 - E: 12:47:07 D: 00:30:00 (Start: 312.0) (End: 1366.0) show more...

vlc ~/Videos/veyepar/pyconza/pyconza2018/dv/cedarwood/2018-10-11/12_17_07.ts :start-time=0312.0 --audio-desync=0

	Raw File	Cut List
	12:17:07		seconds: 312.0 Wall: 12:22:19
Duration	00:30:00
	12:47:07		seconds: 1366.0 Wall: 12:39:53
Comments:
mp4 mp4.m3u	dv.m3u	Split: Sequence:: delete