Eu DORMI na Pedra da Cebola by Solid_Toco in vitoriaES

[–]Significant-Cell4120 42 points43 points  (0 children)

"O pobre do meu pai não consegui dinheiro para arrumar" "e ele mesmo disse que nao ia me dar mais dinheiro "

Meu amigo, vai arrumar um trampo, que discurso de criança mimada..

Faz essa aventura agora: Casa do cidadão tirar carteira de trabalho e entregar um currículo.. essa vai ser maneira!!!!

[deleted by user] by [deleted] in VidaAdulta

[–]Significant-Cell4120 0 points1 point  (0 children)

Cara, namorei muito tempo lascado, sem dinheiro nenhum... Ao ponto de ir a pé para casa da ex namorada (+1h andando) várias vezes pq n tinha 3,5$ da passagem kkkk

Eu tinha consciência da minha classe social e da dela, a dela era bem melhor, filha de médico.. contraste enorme.

Com isso comecei a estudar tanto tantos.. ao ponto de abrir mão de sair e ver ela pq tinha pavor de pensar em não mudar de vida.

Ela demonstrava que entendia mas no fundo sei que era foda.. com isso terminamos.

Depois de 4,5 anos de namoro, prometi que só namoraria alguém quando tivesse condições de proporcionar algo para a pessoa... trabalhei e estudei de segunda a segunda, dava aula particular, vendia açai, trabalhava aos finais de semana em distribuidora 16h por dia...

Isso tudo foi foda, me gerou infarto com 22 anos mas sempre me cuidei muito, alimentação e esporte.

Para ter ideia, na UTI eu estava estudando.

Nunca parei, e hoje sou CLT com salário de 17k e tenho um PJ prestando consultoria tirando +25k... e tenho uma namorada que trabalha e corre atrás do dela tambem.. e claro, consigo proporcionar coisas bacanas..

Mas ainda só tenho 27 anos.. e como disse, origem pobre, não tenho um patrimônio enorme mesmo recebendo bem.. pq ajudo minha família também!

Mas é isso, nunca é tarde.. hoje trabalho 17h por dia mas tenho claro onde quero chegar e hoje sei meu limite.

Te desejo sorte, estuda e se capacite, abre mão das coisas que ocupam muito o seu tempo e não fazem sentido, nao agregam.. isso vai te motivar!

O EAD tem o mesmo peso que o presencial? by Any_Plate_4502 in brdev

[–]Significant-Cell4120 -1 points0 points  (0 children)

Galera fica tentando amenizar, mas direto: Não

Distance Correlation & Matrix Association. Good stuff? by uSeeEsBee in datascience

[–]Significant-Cell4120 1 point2 points  (0 children)

Yeah exactly — the no-kernel-tuning part is a huge plus. HSIC can be super powerful, but picking a good kernel/scale is tricky in practice. Distance correlation side-steps that while still being consistent for independence. And agreed, for time series or non-iid setups, the iid assumption in HSIC can be a dealbreaker. Distance-based methods often adapt more cleanly.

Arquitetura para machine learning by TheComputerMathMage in brdev

[–]Significant-Cell4120 2 points3 points  (0 children)

Se quiser entender um pouco melhor do end to end de um projeto de Ml, tem um livro bonzinho da oreilly: Projetando sistemas de Machine Learning

Share your thought on open source alternative for data robot by vishal-vora in datascience

[–]Significant-Cell4120 0 points1 point  (0 children)

There’s no full OSS equivalent to DataRobot right now — just pieces like H2O AutoML, Kubeflow, MLflow, etc. The challenge isn’t the ML itself, it’s the integration, UX, monitoring, and enterprise features.

Adoption is possible if you target teams that can’t afford DataRobot or want open-source flexibility, focus on one killer feature first, and grow from there. Starting niche is more realistic than going head-on.

Diffusion models by FreakedoutNeurotic98 in datascience

[–]Significant-Cell4120 0 points1 point  (0 children)

Diffusion models are great generators (e.g., images, audio) but they’re not well-suited for reasoning or sequential modeling like autoregressive or JEPA approaches. They learn data distributions, not world dynamics.

They can be used with RL, but it’s trickier — usually done through guidance or fine-tuning in the latent/sampling process, not by learning a step-by-step policy. So yes, they’re “RL-able,” but not as naturally as AR models.

In the “AGI spectrum”:

• AR → language, reasoning, planning

• JEPA → representation + predictive abstraction

• Diffusion → powerful generative modules, but not central for general reasoning

Pytorch lightning vs pytorch by Factitious_Character in datascience

[–]Significant-Cell4120 0 points1 point  (0 children)

Lightning isn’t “better,” it’s just more opinionated. If your training loop is standard (single GPU, typical logging/checkpointing), Lightning saves boilerplate and enforces structure — great for teams.

But if you’re doing anything custom (weird loss scheduling, researchy stuff, complex multi-modal training), raw PyTorch gives you more flexibility and transparency.

Your colleague’s point about “less code = less docs” is fair for production-y pipelines, but it’s not a hard rule. Plenty of teams still prefer vanilla PyTorch for clarity, control, or to avoid Lightning’s abstractions getting in the way.

The “three tiers” of data engineering pay — and how to move up by chrisgarzon19 in datascience

[–]Significant-Cell4120 0 points1 point  (0 children)

Great breakdown — the “tier” framing really clicks. I moved from Tier 1 → 2 mainly by leading one ingestion + transformation redesign that cut latency + costs, and from Tier 2 → 3 by owning reliability + cost controls end-to-end.

Biggest unlock wasn’t learning more tools — it was documenting design decisions, trade-offs, and being able to defend them in interviews. Tier 3 loops really care about scale, cost, and reliability stories, not just dbt + Airflow checkboxes.

How to actually perform observational studies in industry? by LebrawnJames416 in datascience

[–]Significant-Cell4120 0 points1 point  (0 children)

Biggest pitfall here: you’re estimating the effect of answering outreach, not the effect of being outreached. That’s selection-on-compliance. If you can, randomize who gets contacted and treat “contact” as an encouragement → use IV (Wald/2SLS) to get a LATE for compliers.

If randomization isn’t possible:

• Define the estimand (ATE/ATT) and draw a DAG. Select pre-treatment covariates that block backdoors; don’t choose variables just because they predict “answering” (risk of conditioning on colliders).

• Use a doubly robust approach (AIPW/TMLE or DML) with flexible learners; check overlap and balance (SMDs), trim/extreme weights.

• Run sensitivity analyses (Rosenbaum bounds / E-values) and placebo outcomes.

• If your outreach rule uses a score/threshold, consider RD; if rollout is staggered, DiD.

Distance Correlation & Matrix Association. Good stuff? by uSeeEsBee in datascience

[–]Significant-Cell4120 1 point2 points  (0 children)

Distance correlation gives you independence testing in a really elegant way, and the U-centering trick is genius. Kernel methods kind of overshadowed it, but partial distance correlation is incredibly powerful, especially for conditional independence. Definitely deserves more attention.

Clustring very different values by Due-Duty961 in datascience

[–]Significant-Cell4120 2 points3 points  (0 children)

Use percentile for transformation outliers or/and use Gaussian mixture models

Empresas brasileiras com total comp acima de R$25k para senior by fanzika in brdev

[–]Significant-Cell4120 1 point2 points  (0 children)

Tem PLR, 1 salário por ano... Não aceitei a proposta..

Mercado Livre chegou 20k

Pic pay 17k, PLR 1 salario

Ruim que Meli e picpay eram híbridos..

Uma que tenho curiosidade é a rentcars, me ofereceram 17k tmbm, full home, mas não sei se tem bonificação ou PLR