~/talk

Where to Start with Machine Learning

Talkat Develop:Brighton Digital 2020 · 2020-11-02..11-04· [machine-learning]
links:none on file
slides:none on file

vTime demonstrates a working pipeline that turns a photo into a vtag avatar using an image-to-image deep model trained on freely available datasets and GitHub code, producing usable results in about a day. Training needs GPUs with 8–10 GB minimum and the recommended cards are RTX 3070/3080/3090, a home build costs ~£2k–£2.5k versus AWS becoming costlier after 1–4 months. Notable data warning: the CelebA 200k dataset contains biased labels (e.g. an “attractive” tag) that alter outputs like skin tone.

AI-written summary · about

  1. 0:00Introduction
  2. 0:50What is Machine Learning
  3. 3:54Machine Learning in Gaming
  4. 6:25Hardware vs Cloud
  5. 10:41Free Resources
  6. 13:18What to Expect
  7. 17:56Legal Ethical Concerns
~/search
type to search 6,249 conferences, 138,987 speakers and 185,172 talks
~/help
cmdctrl k
search every conference, speaker and series
/
focus the filter search
h
home
c
conferences
s
speakers
e
series
t
light / dark — the status bar button does the same
?
this help
esc
close this, then clear every filter — or just the search, while you are typing in it

Ignored while you are typing. Pages without a filter rail have no search to focus.