Low-code AI tools - are they good? | #datascience #datasciencecareer #careeradvice

Data Science With Marco · Intermediate ·🛠️ AI Tools & Apps ·3y ago

Key Takeaways

Low-code AI tools like Dataiku, Azure ML, and H2O.ai are compared to low-code website builders, highlighting their limitations in customization and the need for data scientists to tailor solutions to specific problems.

Full Transcript

my opinion on low code and no code ds automation tools like dataku azure ml and h2o.ai i mean i compared those to like a low code website builder like wix or squarespace so they're good in some use cases but as soon as you want to go out or customize something you need to know how it actually works and that will probably require a data scientist so i mean they exist they probably have a good reason to exist but it will definitely not replace a data scientist who can you know tailor a solution to a problem
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Low-code AI tools have their use cases, but customization limitations and the need for tailored solutions require data scientists, highlighting the importance of understanding data science automation and the role of data scientists.

Key Takeaways
  1. Evaluate low-code AI tools like Dataiku, Azure ML, and H2O.ai
  2. Identify customization limitations and potential roadblocks
  3. Recognize the need for data scientists to tailor solutions to specific problems
  4. Consider the trade-offs between low-code AI tools and custom solutions
💡 Low-code AI tools are not a replacement for data scientists, but rather a complementary tool that can aid in certain use cases, emphasizing the importance of understanding the strengths and limitations of these tools.

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