Bored with Python, should I learn C++? [D]

📰 Reddit r/MachineLearning

Explore C++ for lower-level computing in ML, understanding its benefits and challenges

intermediate Published 28 Aug 2026
Action Steps
  1. Explore C++ basics using online resources like Codecademy or Coursera to understand its syntax and data structures
  2. Run C++ code snippets to get familiar with its compilation and execution process
  3. Configure a C++ development environment on your machine to start building small projects
  4. Test C++ libraries like TensorFlow C++ API or Caffe to see how they can be used for ML tasks
  5. Compare the performance of C++ and Python for specific ML tasks to understand the trade-offs
Who Needs to Know This

ML engineers and researchers looking to dive deeper into low-level computing may benefit from learning C++, while team members focused on deployment and high-level abstractions may not need this skill

Key Insight

💡 C++ can provide a more detailed understanding of low-level computing in ML, but it requires a significant investment of time and effort to learn

Share This
Ready to dive deeper into #MachineLearning? Consider learning C++ for lower-level computing and understanding the benefits and challenges #ML #Cpp

Full Article

I'm getting pretty bored with Python for ML. With GenAI tools now being able to write very good code, I feel like writing in a high-level language is becoming less interesting to me. Also, it seems like a lot of the focus in ML is shifting toward deployment and inference rather than the architecture or math. I'm not interested in deployment, or what Agentic AI lovers call "building." I want to understand and work with lower-level computing instead.
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