Scale Nucleus VS DEV.to
Compare Scale Nucleus VS DEV.to and see what are their differences
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Scale Nucleus
ML Image Classifier
Aquarium
Prodigy
mlblocks
PerceptiLabs
Machine Learning Playground
Roboflow Universe
DEV.to
WordPress
Medium
Hashnode
Ghost
Drupal
GitHub
Stack Overflow
DEV.toAs a mini-blog, it is a nice alternative for Medium to publish and share information about programming.
However, the community and the organization are biased toward social justice (and they are open to it). You can read its Code of Conduct, it is so vague and politically leads (I prefer a term of service because it defines fair rules for everybody). So it alienates developers that we don't care about politics in pro of people that want to talk about any other topic such as sexuality, how women are unprivileged, and such. It even mandates to use inclusive language. Good grief.
My main complaint is the quality of the community. It is not StackOverflow (so we don't want to ask for an answer here), and most of the top topics are clickbait, such as "how to become a rockstar developer in ... days", "100 tips to become a better programmer" (and it doesn't even talk about programming).
Technically this "mini blog" site allows us to use markdown, and it is okay. However, the whole experience is really basic. Even the template is ugly.
Based on our record, DEV.to seems to be a lot more popular than Scale Nucleus. While we know about 653 links to DEV.to, we've tracked only 2 mentions of Scale Nucleus. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
At Scale we built a tool for model debugging in computer vision called Nucleus (scale.com/nucleus) designed exactly for this, which is free try out if you're curious to see where your model predictions are most at odds with your ground truth. Source: over 4 years ago
To address your point about gathering edge cases, which can also be defined as cases of low model fidelity for our use cases, there is active learning and tools such as Aquarium Learning and Scale Nucleus which make it easy to implement into workflows. Source: about 5 years ago
Def pending(): drafted = open(DRAFTS, encoding="utf-8").read() out = [] for a in api(f"/articles?username={ME}&per_page=100"): if not a["comments_count"]: continue for c in api(f"/comments?a_id={a['id']}"): if c["user"]["username"] == ME or replied_by_me(c): continue if c["id_code"] in drafted: continue ... - Source: dev.to / about 2 hours ago
Katalon True Platform is designed to deliver returns across all four ROI categories through its unified architecture and six purpose-built AI agents, all orchestrated by the Katalon AI Assistant. The model is consistent throughout: AI proposes, humans approve. - Source: dev.to / 3 days ago
The search box on the homepage now runs keyword, semantic, and hybrid search, with a toggle so you can compare and watch them disagree. Type pydub and flip to semantic mode to see it get the answer wrong; flip to hybrid to see it get it right again. The whole thing is a 4 MB lookup table, a tiny document index, and about 300 lines of dependency-free JavaScript, lazy-loaded only when you focus the search box so the... - Source: dev.to / 5 days ago
Start tracking costs from day one with a tool like Tokonomics. Start charging when AI costs exceed 15% of revenue or when you see a clear 10x+ variance between your lightest and heaviest users. Early-stage startups can absorb costs temporarily for growth, but set the expectation early that AI features have usage-based pricing. - Source: dev.to / 5 days ago
Python -m pip install unlimited-search Unlimited-search read https://dev.to --max-content-chars 1500. - Source: dev.to / 12 days ago
ML Image Classifier - Quickly train custom machine learning models in your browser
WordPress - WordPress is web software you can use to create a beautiful website or blog. We like to say that WordPress is both free and priceless at the same time.
Aquarium - Improve ML models by improving datasets theyโre trained on
Medium - Welcome to Medium, a place to read, write, and interact with the stories that matter most to you.
Prodigy - Radically efficient machine teaching
Hashnode - A friendly and inclusive Q&A network for coders