The hottest Wikipedia Substack posts right now

And their main takeaways
Category
Top Culture Topics
Franz likes to code 39 implied HN points 05 Sep 24
  1. If you're having trouble with the Google Trends Python package, you can switch to using Wikipedia's page view statistics instead. It's a reliable and official way to get data on search trends.
  2. Wikipedia provides a rich API that allows you to fetch daily or hourly view counts for specific articles. This can help analyze how topics gain interest over time.
  3. You can use a simple Python code to find the page views for any Wikipedia article, making it easy to replace Google Trends in your research and get the data you need.
Links I Would Gchat You If We Were Friends 0 implied HN points 02 Feb 16
  1. Beware of fake profiles in online dating sites, the use of fake bots is widespread and many people have fallen victim to them.
  2. Wikipedia can be a predictor of the presidential race and wikipedians have a significant influence on public opinion.
  3. Algorithms are both simpler and more complex than they seem, reading up on them could be beneficial.
Links I Would Gchat You If We Were Friends 0 implied HN points 23 Jun 14
  1. Finding one's hometown using online maps is possible, as seen in the story of Saroo Brierley.
  2. Wikipedia may seem chaotic, but it actually faces challenges due to bureaucratic processes.
  3. David Sedaris, the popular essayist, once displayed obsessive behavior with his Fitbit, walking an incredibly high number of steps in a day.
just learning data science 0 implied HN points 29 Jan 24
  1. Wikipedia may not be the best place for beginners to learn Data Science and Machine Learning due to the unordered topics and high entry level.
  2. The concept of Likelihood function on Wikipedia made it difficult initially due to the absence of input variables, which is a crucial aspect to understand.
  3. Models in machine learning can vary from deterministic with input variables to non-deterministic like a coin flip, showing the wide range of possibilities for machine learning models.
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