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.
