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#machine-learning-engineer — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #machine-learning-engineer, aggregated by home.social.

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  1. What's bigger than #chatgpt 4 for #datascientist 's and #machinelearningengineer 's working in #structureddata ? I'd say its #xgboost 2.0! Now out with 2.0.2 (I never trust a .0 release 😉 ). #llm get all the #aihype these days, but gradient boosting is the revolutionary tech that some say "killed data science" by making it too easy! 2.0 Includes enhancments like #gpu support and learning to rank, not to mention supporting the latest pandas. github.com/dmlc/xgboost/releas

  2. What's bigger than #chatgpt 4 for #datascientist 's and #machinelearningengineer 's working in #structureddata ? I'd say its #xgboost 2.0! Now out with 2.0.2 (I never trust a .0 release 😉 ). #llm get all the #aihype these days, but gradient boosting is the revolutionary tech that some say "killed data science" by making it too easy! 2.0 Includes enhancments like #gpu support and learning to rank, not to mention supporting the latest pandas. github.com/dmlc/xgboost/releas

  3. #AI Model Fit Obsession Disorder (MFOD) : A #pathology afflicting a #datascientist or #machinelearningengineer in which they think their job is to call the function model.fit, and that's it. The disorder is characterized by a lack of curiosity about whats inside their #blackbox, a belief that only good things happen from calling the model.fit function, and disdain for understanding #ai by means other than the mean square error. #aihype #datascience #machinelearning

  4. #AI Model Fit Obsession Disorder (MFOD) : A #pathology afflicting a #datascientist or #machinelearningengineer in which they think their job is to call the function model.fit, and that's it. The disorder is characterized by a lack of curiosity about whats inside their #blackbox, a belief that only good things happen from calling the model.fit function, and disdain for understanding #ai by means other than the mean square error. #aihype #datascience #machinelearning

  5. As a native #newyorker I'm a @nytimes reader. As a #datascientist and #machinelearningengineer I believe we are reaching new highs in the #aihype cycle as evidenced by the daily parade of #AI articles! Six major articles in just the last week!

    My fav was the "True Threat of Artificial Intelligence": It says the threat is economic dysfunction due to the dynamics of unregulated #tech rollout by #venturecapital backed firms.

    #datascience #machinelearning #artificialintelligence

  6. As a native #newyorker I'm a @nytimes reader. As a #datascientist and #machinelearningengineer I believe we are reaching new highs in the #aihype cycle as evidenced by the daily parade of #AI articles! Six major articles in just the last week!

    My fav was the "True Threat of Artificial Intelligence": It says the threat is economic dysfunction due to the dynamics of unregulated #tech rollout by #venturecapital backed firms.

    #datascience #machinelearning #artificialintelligence