The hottest Data Mining Substack posts right now

And their main takeaways
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Top Technology Topics

We Are What We Click

Diane Francis • 399 implied HN points • 04 Mar 21
🕹 Technology Privacy Surveillance Big Tech Data Mining Social media
  1. Big Tech companies collect and sell our online data, which makes them extremely wealthy and invades our privacy. It’s important to be aware of how much information we share online.
  2. Cookies and algorithms create 'filter bubbles' that limit our exposure to different views and ideas. This can lead to social isolation and political division.
  3. We can take steps to protect our privacy online, like blocking cookies and clearing our search history. However, government regulations are also needed to help keep our data safe.

Data Science Weekly - Issue 10

Data Science Weekly Newsletter • 19 implied HN points • 30 Jan 14
🕹 Technology Data science Machine Learning AI Data Mining Statistics
  1. Data mining can help predict which countries will win medals in the Winter Olympics. It can reveal trends and reasons behind particular nations' success.
  2. Deep learning aims to make computers think like humans. It showcases the progress in teaching machines to learn and improves how they process information.
  3. Data science plays a crucial role in various industries, like Foursquare and New York's Fire Department, to analyze data and improve services or predict events.

Descriptive Statistics with Orange

rtnF • 0 implied HN points • 01 Apr 23
🕹 Technology Data Mining Data Analysis Statistics
  1. Descriptive statistics with Orange allows for easy data analysis without needing spreadsheet equations or code.
  2. The mean and median provide insight into average building height, helping to understand outlier influence on data.
  3. Understanding dispersion, like the coefficient of variation, reveals how data points spread out relative to the mean.

Microsoft, Timnit Gebru, and Google AI

Technology Made Simple • 0 implied HN points • 17 Dec 21
🕹 Technology Artificial Intelligence Machine Learning Data Mining
  1. Microsoft made significant progress in NLP with their language model scaling on GLUE and SuperGLUE benchmarks, but the lack of transparency in their publication raises questions about replicability and sharing knowledge in research.
  2. Timnit Gebru, a prominent figure in AI, established the Distributed AI Research Institute to conduct independent, community-rooted AI research free from Big Tech's influence, funded by donations.
  3. The issues surrounding Microsoft's publication practices and Gebru's new research institute highlight the importance of understanding the dynamics in the machine learning research space and taking steps to stay informed and educated about the field.

As someone who cares about privacy, how do I feel working for Google?

Thái | Hacker | Kỹ sư tin tặc • 0 implied HN points • 27 Jan 16
🕹 Technology Privacy Data Mining Internet Security Digital Advertising
  1. Google invests heavily in internet security and privacy innovations.
  2. Google's data mining practices for personalized ads are common, but they offer users many choices to control their privacy.
  3. Google emphasizes user privacy by encrypting private data, providing privacy controls, and offering ads-free services.
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5 Things NLU Engines Are Really Good At

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 03 Apr 23
🕹 Technology AI NLP Chatbots Machine Learning Data Mining
  1. NLU engines make data entry super easy with no coding needed. You can just click and put in your data without worrying about complicated setups.
  2. Intents, or the goals of what users want, are flexible and can adapt to different classes or categories. This helps in understanding user requests better.
  3. Entities, which represent specific items or information, have improved a lot. Better detection of these lets chatbots gather information without having to ask the user again.