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.
LOL (lots of links) 963 implied HN points 16 Oct 23
  1. The world is full of strange and interesting wonders like a potato Airbnb and historic animal obituaries.
  2. There are individuals who curate unique collections like a NYC garbageman's trash museum and an online vacuum cleaner museum.
  3. Excessive noise, like from trains, can have a significant impact on mental health and well-being.
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.
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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