Scikit-learn Reviews

Bright Data Reviews

1. Sam Mitchell

   · Owner at KittenProperties · over 2 years ago
   Mixed feelings

   We used their DC proxies and Residential proxies. Resi proxies were having quite low success rate. We had to use resi solution from other proxy providers. Unblocker didn't work well either also it was way too expensive.

   🏁 Competitors: Decodo, NetNut.io

   👍 Pros:    Cheap dc proxies

   👎 Cons:    Quite expensive|Residential proxies are worse than competitiors

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 / about 2 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 / 2 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 / 2 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 / 3 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 / 5 months ago

Bright Data mentions (45)

• Precursor

  Happy to offer a counter of some great products for anti-bot defeat: https://brightdata.com/ https://www.zenrows.com/ https://www.capsolver.com/ https://scrapfly.io/ hundreds of millions of residential ips, human browser fingerprints, custom browser binaries, auto solve of turnstyle, recaptcha v3, kasada, datadome, AWS WAF, etc if they come up. - Source: Hacker News / 7 days ago

• Best Web Scraping Tools in 2026: A Hands-On Comparison of the Top 10

  The best web scraping tools 2026 leaderboard hasn't changed; the gap has narrowed. Bright Data remains the safest bet for any team that wants to spend time on the data, not on the scraping. The 660-scraper library, 400M-IP network, pay-per-success pricing and unlimited concurrency are still uncontested at the high end. - Source: dev.to / 3 months ago

• The Economics of Web Scraping: How Consultancies Price Data Extraction and Manage Scope Creep

  Infrastructure Pass-Through (OpEx) Data extraction at scale is infrastructure-heavy. Bypassing modern Web Application Firewalls (WAFs) requires high-quality residential proxies, CAPTCHA solvers, and substantial browser-automation compute resources. Services like Bright Data charge significantly by the gigabyte for premium residential IPs. These variable infrastructure costs must be passed directly to the client,... - Source: dev.to / 3 months ago

• LinkedIn Scraping Is Dead: 5 Legal, ToS-Safe Alternatives That Actually Work in 2026

  Bright Data has successfully defended web scraping in U.S. Courts and offers LinkedIn datasets pre-collected and ready to download. LinkedIn profile data on their dataset marketplace runs around $250 per 100,000 records. The freshness caveat is real: bulk datasets are snapshots, not real-time. If you need current job titles on a rolling basis, you're better with an enrichment API than a one-time dataset pull.... - Source: dev.to / 3 months ago

• Building a Live AI Market Research Terminal: How Bright Data and Convex Replace Polling With Real-Time Everything

  Bright Data built an open-source demo that solves this. It's called the Signal Terminal, a financial research tool built around that problem. - Source: dev.to / 5 months ago