Top KDnuggets tweets, Sep 02-08: Training alone is never enough to generate effective supervised machine learning models

Top KDnuggets tweets, Sep 02-08: Training alone is never enough to generate effective supervised machine learning models

Also: Tensorbook, a #DeepLearning laptop; 5 Concepts Every #dataScientist Should Know: Multicollinearity, encoding, sampling, error, and storytelling; Top 20 #Python AI and #MachineLearning #OpenSource Projects; How To Decide What Data Skills To Learn


Most popular @KDnuggets tweets for Sep 02-08 were:

Most Retweeted, Favorited & Viewed:
Training alone is never enough to generate effective supervised machine learning models. https://t.co/koABOgZaBj https://t.co/M47SzFCzXh

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Top 10 most clicked Tweets

  1. Tensorbook, a #DeepLearning laptop https://t.co/997Gijf7Gn https://t.co/iKIe58BmIu
  2. Training alone is never enough to generate effective supervised machine learning models. https://t.co/koABOgZaBj https://t.co/M47SzFCzXh
  3. 5 Concepts Every #dataScientist Should Know
    Multicollinearity, encoding, sampling, error, and storytelling. https://t.co/CYnMgiJeWN https://t.co/cZwwz2sxRP
  4. Top 20 #Python AI and #MachineLearning #OpenSource Projects #KDN https://t.co/z0YGkpqajH
  5. How To Decide What Data Skills To Learn – KDnuggets https://t.co/2l1fNotjsV https://t.co/a57e6uejR0
  6. Five #MachineLearning Paradoxes that will Change the Way You Think About Data https://t.co/5KSFcX7RYO https://t.co/8Ilpx9WRqt
  7. Must Read: Modern #DataScience Skills: 8 Categories, Core Skills, and Hot Skills https://t.co/EBcsSpJj5m https://t.co/L8JYuZyUuW
  8. #GPT3 wrote this entire @guardian article. The task: To convince humans that robots come in peace and will not destroy humans. Are you scared, human? @OpenAI https://t.co/HsqJQkUknM https://t.co/nuYsktnBpY
  9. Here is What I’ve Learned in 2 Years as a Data Scientist – KDnuggets https://t.co/t0miIz0dxA https://t.co/4mybTOAHqb
  10. Four foundational approaches for linear regression. https://t.co/D9aN7LUlow https://t.co/NMICLbPzaY

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