[greenonion]

You got me a bit confused here. If I understand correctly what you 're saying, you 're still using Python for prototyping the core algorithms and C++ in actual production systems. I'm not saying Python is not good for production systems in general, I'm wondering whether it is good enough for real-world implementations of machine learning algorithms.

Also, I believe most people would consider Java as an alternative to C++, hence all the Java-based Apache projects, such as Mahout, Solr etc.

[law]

I use Python in production for text pre-processing and other ETL-related processes, which is part of a larger reinforcement learning approach. Additionally, I use Python to prototype the core ML algorithms, which I sometimes re-implement in C++. However, for many of those algorithms, numpy actually performs identically to BLAS in C++.

[greenonion]

I get it now, thanks. It's very interesting, maybe I will give Python for ML a chance!