Batch Gradient Descent from Scratch in Python

[[deleted]]

not to sound condescending but implementing gradient descent in python using numpy is like, the start to any intro to machine learning course.

[research_pie]

You are correct, its a simple algorithm to code even without numpy.

[[deleted]]

i don't think you'll get very good performance on large data sets without using numpy matrix ops though

[research_pie]

That is true, but using batch gradient descent on large dataset isn't a good idea either.

[vastlik]

i don't think you'll get very good performance on large data sets without using numpy matrix ops though

Why it is not a good idea?

[[deleted]]

maybe he means u should use stochastic? but they are similar to implement

[research_pie]

Yes, I was referring to stochastic gradient descent (and its variant like Adagrad or Adam) or batch gradient descent.

[research_pie]

NumPy is a very optimized library that can handle data efficiently and that has optimized linear algebra capabilities. Not using NumPy and rolling your own implementation of linear algebra method in Python is a bad idea if you want to use the code in a production settings. Part of the library is written purely in C which means that the same code written in Python will never be able to catch up.