Chanran Kim

Vision AI Research Development - Republic of Korea

Passionate about solving human problems, Chanran’s main interests are computer vision and natural language processing while using machine learning and deep learning. He’s written a book on transfer learning and he often gives lectures on it.

Today, Chanran is running Pseudo Labs, a machine learning community he founded in 2020. Pseudo Labs is all about sharing knowledge on machine learning and deep learning studies for free, offering Kaggle meetups, code sharing and other events in the Republic of Korea.

When Chanran isn’t running hackathons for Pseudo Labs, you’ll find him watching Premier League soccer matches or honing his food photography (pop over to his Instagram to see some mouth-watering shots).

As a Z by HP Global Data Science Ambassador, Chanran's content is sponsored and he was provided with HP products.

Great things are not done by impulse, but by a series of small things brought together.

Vincent van Gogh


  • What can you now do on a Z that you couldn’t do before?

    Before I could only train a model in instant, but now long-term projects are also possible.

  • What is the next thing you want to learn or experiment with on your Z?

    I’m interested in trying neural architecture search and hyperparameter search.

  • What’s your favorite Z feature?

    How compact it is for the impact it has.

My current gear provided by Z
  • HP Z4

    From design to visualization, our most popular Z desktop accelerates a wide range of pro apps. With high-performance processor options, plus dual extreme graphics support, you get all you need, nothing more.

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    Never has so much power been engineered into such a sleek package. Keep your best talent creating on the latest tech with the new benchmark for mobile workstations.

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  • Dual Z27

    Experience extraordinary, precise color and see more of your projects at once on a display with stunning 4K resolution.

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  • Preloaded Software Stack

    Save countless days installing, configuring and maintaining your data science environment by choosing the preloaded data science software stack.

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