In this video, I share my journey of deploying the same AI project with both Go and Python, highlighting the challenges, successes, and performance differences.
🤔 Takeaways:
Go excels in response times, scalability, and resource management.
Some data science libraries might be less efficient in Go compared to Python.
Consider switching to Go for performance gains when Python hits traffic limits.
🚨 Important Note:
While Go may not cover all data science libraries, its strengths shine in specific scenarios. Explore the performance gains and make a strategic decision based on your project's requirements.
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