Theano is a software package which allows you to write symbolic code and compile it onto different architectures. It's especially good for machine learning techniques which are CPU-intensive. I’m going to show you the basic principles of Theano, including common difficulties which come up. We’ll see how to use Theano and get all the benefits from parallelization. Topics covered in this talk will be symbolic variables, functions, gradients and debugging. As a result of this talk you'll be able to build your own neural network.
NumPy is the fundamental Python package for scientific computing. However, being efficient with NumPy might require slightly changing how you write Python code. I'm going to show you the basic idioms essential for fast numerical computations in Python with NumPy. We'll see why Python loops are slow and why vectorizing these operations with NumPy can often be good.
This is an introductory course in machine learning (ML) that covers the basic theory, algorithms, and applications.
This is an introductory course in Python.