Ahrefs Reviews

1. Cyra Brown

   | Owner at Beginu | about 2 years ago
   Excellent for discovering low competition keywords

   I've enjoyed using Ahrefs to inform content creation due to their keyword explorer being so useful for finding low difficulty keywords. I do prefer the legacy version of their site explorer in comparison to the new format so I hope that they do not retire certain elements of the platform.

   🏁 Competitors: SEMRush

Scikit-learn Reviews

Ahrefs mentions (111)

• Ahrefs vs Semrush | Which One is Better

  Ahrefs is an online software suite used for SEO and content marketing. You can discover the most valuable keywords to target, see the content that's ranking for those terms, find link building opportunities, analyze your competitors' sites. The advanced application tracking system lets its users track search engine rankings and positions. - Source: dev.to / about 1 month ago

• How to Identify Content Refresh Candidates, In Detail

  Next up, let's find articles ranking between 4 and 15.  To do this, you'll log into Ahrefs and use site explorer on the target site, navigating to "top pages."  Here's what that looks like for our property, makemeaprogrammer.com. - Source: dev.to / 5 months ago

• I figured out about the backlinking strategy that you can apply to your SEO.

  Did you know that securing backlinks from industry giants like Ahrefs, SEMrush, Get First Page, and Search Engine Land can be a game-changer for your online presence? 📈💻. Source: 6 months ago

• 2024 Google SEO Checklist: A List of Tips for Website Optimization

  Analyze competitors’ link configuration files (analyze and study competitors’ external link configuration, which can be detected through Ahrefs analysis tool);. Source: 7 months ago

• Why My Domain Authority Dropped

  Even When I checked my site on https://ahrefs.com/ he shows approx 350 domain with high DA and PA. Source: 7 months ago

Scikit-learn mentions (28)

• How to Build a Logistic Regression Model: A Spam-filter Tutorial

  Online Courses: Coursera: "Machine Learning" by Andrew Ng EdX: "Introduction to Machine Learning" by MIT Tutorials: Scikit-learn documentation: https://scikit-learn.org/ Kaggle Learn: https://www.kaggle.com/learn Books: "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman By... - Source: dev.to / 3 months ago

• Link Prediction With node2vec in Physics Collaboration Network

  Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / 12 months ago

• WiFilter is a RaspAP install extended with a squidGuard proxy to filter adult content. Great solution for a family, schools and/or public access point

  The ML component is based on scikit-learn which differentiates it from purely list-based filters. It couples this with a full-featured wireless router (RaspAP) in a single device, so it fulfills the needs of a use case not entirely addressed by Pi-hole. Source: about 1 year ago

• PSA: You don't need fancy stuff to do good work.

  Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive... Source: about 1 year ago

• Help on using R for Machine Learning?

  Scikit-learn is a machine learning library that comes with a number of pre-built machine learning models, which can then be used as python wrappers. Source: over 1 year ago