DataTalks.Club

Similarities and Differences between ML and Analytics - Rishabh Bhargava

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We talked about:

  • Rishabh's background
  • Rishabh’s experience  as a sales engineer
  • Prescriptive analytics vs predictive analytics
  • The problem with the term ‘data science’
  • Is machine learning a part of analytics?
  • Day-to-day of people that work with ML
  • Rule-based systems to machine learning
  • The role of analysts in rule-based systems and in data teams
  • Do data analysts know data better than data scientists?
  • Data analysts’ documentation and recommendations
  • Iterative work - data scientists/ML vs data analysts
  • Analyzing results of experiments
  • Overlaps between machine learning and analytics
  • Using tools to bridge the gap between ML and analytics
  • Do companies overinvest in ML and underinvest in analystics?
  • Do companies hire data scientists while forgetting to hire data analysts?
  • The difficulty of finding senior data analysts
  • Is data science sexier than data analytics?
  • Should ML and data analytics teams work together or independently?
  • Building data teams
  • Rishabh’s newsletter – MLOpsRoundup


    • Links:

    • https://mlopsroundup.substack.com/
    • https://twitter.com/rish_bhargava


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