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Strong Analytics

Company blog · strong.io/blogdataai

Strong Analytics is the company blog at strong.io, writing about data and ai. Since 2016, 5 different Hacker News readers have linked it 21 times, most often “Predicting user behavior: Using machine learning to identify paying customers”. No feed was found, so read it on the site itself.

No feed foundVisit the blog
21mentions?
5HN people?
2016–2022first – last linked?
Links on Hacker News per year · peak 9 in 2016

We specialize in bringing data science, machine learning, and artificial intelligence projects to life through thoughtful design and rigorous engineering. We collaborate with top organizations to design, build, and deploy custom products and solutions.

Most-linked posts?

  1. Predicting user behavior: Using machine learning to identify paying customers
    3 people · 3 mentions · first linked 2016-06-14

What Hacker News says?

  1. At our data science company, we're building a marketing automation platform that uses deep reinforcement learning to optimize email marketing campaigns. Marketers create their messages and define their goals (e.g., purchasing a product, using an app) and it learns what and when to message customers to drive them towards those goals. Basically, it turns marketing drip campaigns into a game and learns how to win it :)…

    Comment linking /blog/optimail-email-marketing-artificial-intelligence

    on “Ask HN: Where is AI/ML actually adding value at your company?”
  2. Submitted Computer Vision at the Olympics: Tracking Sprinter Speeds as a story · 12 points

    HN discussion
  3. Strong Analytics | Chicago, IL | Full-time Data Scientists, Data Engineers | https://www.strong.io We help companies integrate state-of-the-art machine learning into their products, internal tools, and infrastructure. We've designed, built, and deployed products in the automotive space, pharma, gaming, retail, tech, and many other verticals. Requires an advanced degree (M.S./Ph.D.) in a quantitative science and 1+ y…

    Comment linking /

    on “Ask HN: Who is hiring? (December 2019)”
  4. Submitted Show HN: My friends and I started a data science consulting firm after our PhDs as a story · 8 points

    HN discussion
  5. Submitted Introducing Optimail: Email marketing powered by artificial intelligence as a story · 5 points

    HN discussion
  6. Submitted Predicting user behavior: Using machine learning to identify paying customers as a story · 5 points

    HN discussion
  7. Submitted Five things every startup should be doing with its data as a story · 4 points

    HN discussion
  8. Submitted Use machine learning to identify paying customers before they subscribe (2016) as a story · 3 points

    HN discussion
  9. Submitted Free data science audit: How does your organization's data strategy stack up? as a story · 3 points

    HN discussion
  10. Submitted Customer Lifetime Value: How to Avoid Common Pitfalls and Build Smarter Metrics as a story · 3 points

    HN discussion
  11. Submitted Deep neural networks go to the movies as a story · 3 points

    HN discussion
  12. Submitted Landing page science: Optimizing the conversion rates of 10k+ landing pages as a story · 3 points

    HN discussion
  13. Submitted Beyond pattern recognition: How to approach causal questions properly as a story · 2 points

    HN discussion
  14. Submitted Designing, building, and shipping machine learning solutions: Three principles as a story · 2 points

    HN discussion
  15. Submitted Movie ratings: Do critics and fans see eye-to-eye? as a story · 2 points

    HN discussion
  16. Submitted Edge Machine Learning: From PoC to Real-World AI Applications as a story · 1 points

    HN discussion
  17. Submitted The state of enterprise machine learning (2020) as a story · 1 points

    HN discussion
  18. Submitted Endogenous Gridpoints for Tax Policy Evaluation as a story · 1 points

    HN discussion
  19. Submitted Bias in machine learning: We can do better as a story · 1 points

    HN discussion
  20. Submitted Predictive Model ROI ($) Calculator as a story · 1 points

    HN discussion
  21. Submitted How we use machine learning to identify paying customers before they subscribe as a story · 1 points

    HN discussion

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