8 results for “mew_zh”
Saiu o teaser do da estreia do bloco C de Pokémon TCG Pocket: Fusão Dupla!
Olá pessoal, tudo bem com vocês? Estão aproveitando os pacotes de Pokémon MEGA Deluxe? Eu já fiz um bom farm abrindo pacotinhos deste se
#Jogos #Mobile #Pokmon #TCG #blastoise #Charizard #DualFusion #FestaPikachu #fuecoco #FusoDupla #Greninja #MegaDragonite #MegaMewtwoX #Mew #PikachuParty #venusaur
Aus aktuellem Anlass und immer wieder passend:
"das Kapital [ist] von Kopf bis Zeh, aus allen Poren, blut- und schmutztriefend"
"(...) Das Kapital hat einen Horror vor Abwesenheit von Profit oder sehr kleinem Profit, wie die Natur vor der Leere. Mit entsprechendem Profit wird Kapital kühn. Zehn Prozent sicher, und man kann es überall anwenden; 20 Prozent, es wird lebhaft; 50 Prozent, positiv waghalsig; für 100 Prozent stampft es alle menschlichen Gesetze unter seinen Fuß; 300 Prozent, und es existiert kein Verbrechen, das es nicht riskiert, selbst auf Gefahr des Galgens. Wenn Tumult und Streit Profit bringen, wird es sie beide encouragieren. (...)"
Karl Marx, MEW, Bd. 23, S. 788, Fußnote 250
Quelle: trueten.de
#CapitalismIsADeathCult #Mietenwahnsinn #Vergesellschaftung #GrundgesetzParagraf15 #DeutscheWohnenEnteignen #Gemeineigentum
SHOW ME WHAT YOU GOT: From Behaviour to Recommendations in C#
In Part 2 of this series (apparently 🤷🏼) I move from characterising entities using vector representations to actually recommending actions/content based on those representations.
It's really an 'ML without the models' type approach; we can use the semantics around recommendation systems to teach quite complex ML-related concepts in a practical way…
https://mostlylucid.net/blog/show-me-what-you-got-part2-building-relevance
I also reworked part 1 to fit better into the series so if you've read that part 2 might seem to be repeating some content from the earlier draft.
https://mostlylucid.net/blog/show-me-what-you-got-streaming-recommendations
Umm...this slightly got away from me. https://mostlylucid.net/blog/show-me-what-you-got-streaming-recommendations
About 7,500 words! I really wanted to explain how recommendation systems work and intersect with embeddings and more MLish concepts - including streaming compression, emergent patterns etc...
Ah well...40 minute read it is!
Part 2 is a crazy idea for a generalizable recommendation system you can use anywhere.
Building Part 2 of this article https://mostlylucid.net/blog/show-me-what-you-got-streaming-recommendations - a general purpose realtime streaming recommendation engine. What's *fun* is that it's not just a 'recommend next product' thing...the demo will also show it as. apredictive system admin agent (with no LLM!) 🤓
Series has been fun. Here's a small extra part. How you can use decision models to allow vector based recommendation against pretty much anything from tone to intent...
SHOW ME WHAT YOU GOT (Part 1.5): Vectorise Anything With Decision Models
https://mostlylucid.net/blog/show-me-what-you-got-part1-5-questions-as-coordinates
Bit of a longer post today. Circling back to an article I wrote a while ago about emergent audience segmentation and realised I hadn't covered the basics, so...
SHOW ME WHAT YOU GOT: A Primer on Recommendation Systems in an AI World
https://mostlylucid.net/blog/show-me-what-you-got-streaming-recommendations
Where I go over the history of recommendation systems as well as how AI/ML changes what's possible. This will be the first part in how to build a *streaming* recommendation system (for anything really) using embedding 'like' techniques to characterise user interactions to provide better recommendation systems in everything from ecommerce to social media.
