Theano is a Python library created by a machine learning group in Montreal and is often associated with deep learning, although that is not necessarily its core purpose. Theano is tightly integrated with NumPy and can run code on CPU or GPU. If you are interested in the GPU option, refer to the documentation listed in the See also section. Theano also supports symbolic differentiation through symbolic variables.
According to the its documentation, Theano is a cross between NumPy and SymPy. It is possible to implement machine learning algorithms with Theano, but it's not as easy or convenient as using scikit-learn. However, you may get the potential advantages of higher parallelism and numerical stability.
In this recipe, we will perform linear regression of temperature data using gradient descent. Gradient descent is an optimization algorithm that we can use in a regression context to minimize fit residuals. The gradient measures how steep a function is. The algorithm...