Materials for the NextAI Technical Stream Course on Machine Learning
Notebooks 1 - 4 cover pre-requisite material and are intended to be reviewed before immersion week.
Notebooks 5 - 8 will be covered during immersion week.
Python is established as a leading choice in scientific computing, and in particular, in machine learning. Compared to its competitors (e.g. Matlab), it’s open-source and free! Thanks to a stable numerical base called Numpy which can take advantage of low-level accelerated libraries like the Intel Math Kernel Library (Intel MKL), one can get C-like speeds but with far less programming overhead than compiled languages.
We’ll be using Python for examples in this course.
The so-called "scientific Python" suite consists of a number of tools, including but not limited to:
- Numpy: fundamental package for scientific computing, array data structures and operations
- Scipy: various indispensable tools for math, science, and engineering (depends on Numpy)
- Matplotlib: easy plotting and visualization, Matlab-style
- IPython: Matlab-like interactive shell
Building these libraries on your own is often a hassle, so we recommend using an off-the-shelf distribution. Continuum Analytics' Anaconda has everything we need (and more) for this class. It's cross-platform and completely free for basic use. This will be our recommended way of installing Python and the required libraries for the course.
The easiest way to run the notebooks is to click on the "launch binder" button at the top of this page.
Alternatively, you can download and run the notebooks on your own computer. In this case, the recommended setup procedure is as follows:
- Download and install Anaconda (Python 3.7 version)
- Read about Managing environments
- Examine the YAML environment file
environment.ymlwhich contains dependencies for the course (and examine it in a text editor so you see what's going on) - Create a new environment based on the YAML file:
conda env create -f environment.yml - Activate your new Python environment:
source activate nextai - Start jupyter from this directory:
jupyter notebook