Based on our record, Google Cloud TPU should be more popular than machine-learning in Python. It has been mentiond 3 times since March 2021. We are tracking product recommendations and mentions on Reddit, HackerNews and some other platforms. They can help you identify which product is more popular and what people think of it.
U don't know anything and need to read more about scripting, programming, and machine learning before you can try that AI pseudocode bs. - Source: Reddit / 14 days ago
It’s now the standard language for data science & machine learning. - Source: dev.to / about 2 months ago
Actually, that's done with TPUs which are more efficient: https://cloud.google.com/tpu. - Source: Reddit / 3 months ago
TPU training uses Google silicon and is thus a true deep learning alternative to Nvidia. - Source: Reddit / 4 months ago
The server choice really depends on how much CPU and RAM the requests take, how many users will be hitting the server, etc. You can start with a $5/month Digital Ocean server (or AWS or Google) and see if that works for you. Or you can outsource the server administration to Amazon or Google if you don't want to deal with it or need specialized tpu hardware. - Source: Reddit / 6 months ago
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
BigML - BigML's goal is to create a machine learning service extremely easy to use and seamless to integrate.
Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.
python-recsys - python-recsys is a python library for implementing a recommender system.
GoLearn - GoLearn is a machine learning library for Go that implements the scikit-learn interface of Fit/Predict.
IBM Watson Machine Learning - IBM Watson Machine Learning Service enables you to create, train, and deploy self-learning models using an automated, collaborative workflow.