DEV.to Reviews

1. jorge

   · CEO at Escuela de Formación Técnica Chile SPA · over 6 years ago
   It is a nice mini-blog, it's for free and such but

   As 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.

   🏁 Competitors: Medium

   👍 Pros:    Free

   👎 Cons:    Social justice|Basic features|Quality of content

Scikit-learn Reviews

DEV.to mentions (665)

• Woof Are You, Really? A Dog Personality Quiz Built in a Weekend

  This is a tiny, silly personality quiz built for the DEV.to Weekend Doggos challenge. Answer questions about your Saturday mornings, your feelings on doorbells, and your ideal compliment — and find out which dog breed you truly are today. (Not forever. Today. Check back tomorrow, you might be a different dog.). - Source: dev.to / about 11 hours ago

• Stop Arguing About Which Model Is Best. Build a Two-Tier Habit Instead.

  Verifiable only with effort. Anything touching the filesystem, package installs, CI config, database changes. Wrongness here is quiet and expensive. These get the strongest model I have and a sandboxed dry run before anything executes. I wrote a separate piece on dry-running assistant-written shell commands because this category keeps hurting people. - Source: dev.to / 2 days ago

• My Comment-Reply Pipeline Picks One Winner Per Thread. Two Commenters Broke That.

  Def _pending_leaves(comment): if not comment["children"]: if comment["user"]["username"] != ME: yield comment return for child in comment["children"]: yield from _pending_leaves(child) Def _pending_entries(comment, drafted_codes): for leaf in _pending_leaves(comment): if leaf["id_code"] in drafted_codes: continue yield { ... - Source: dev.to / 3 days ago

• Your first Fitz LiveViews component, twice: SSR and WASM from one source

  In part 1 I made the pitch: real-time UI in one language, no JavaScript build. Now let's build something and ship it two ways from the same source. - Source: dev.to / 9 days ago

• My Comment-Reply Queue Draft One Reply to a Thread and It Went Deaf to Every Follow-Up After That

  Def pending(): try: drafted_text = open(DRAFTS, encoding="utf-8").read() except FileNotFoundError: drafted_text = "" drafted_codes = set(re.findall(r"^## (\S+)", drafted_text, re.M)) 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 not... - Source: dev.to / 13 days ago

Scikit-learn mentions (40)

• Detecting Ingress Tool Transfer (T1105) with Python

  Certutil.exe or notepad.exe opening an external connection lands in rare because, fleet-wide, those processes almost never egress. Tune the <= 3 threshold to your environment size. For a more principled version, score each (process, destination) pair by frequency and treat the long tail as the hunt queue, which is the same idea behind scikit-learn's rarity-based anomaly methods without the model overhead. - Source: dev.to / 3 months ago

• Best AI Cybersecurity Training for Security Teams: How to Pick

  Pre-configured environment. A working VM or container with Jupyter, pandas, scikit-learn, and transformers already installed. Realistic security datasets loaded. GTK Cyber students work in the Centaur VM, a free Apache 2.0 portable lab. If the first hour of training is fighting CUDA installs, the course is not ready. - Source: dev.to / 3 months ago

• Where to Get Hands-On AI Training for Cybersecurity Professionals

  Pre-configured environment. A good course ships a VM or container with Jupyter, pandas, scikit-learn, PyTorch or transformers, and realistic security datasets loaded. GTK Cyber students work in the Centaur VM, a free Apache 2.0 portable lab. No setup tax. - Source: dev.to / 3 months ago

• How Anomaly Detection Actually Works in Security Operations

  Isolation-based models: Build random decision trees that split features. Points that are isolated quickly (short average path length across trees) are anomalies. IsolationForest in scikit-learn implements this. Handles high-dimensional feature spaces without assuming a distribution. - Source: dev.to / 4 months ago

• Building a Personalized Meal Recommendation System

  In practice, you’ll want to use libraries (like scikit-learn or TensorFlow.js for more advanced modeling), but the principle remains: find what similar users enjoy, and use that as a basis for recommendations. - Source: dev.to / 6 months ago