Course Materials: Machine Learning, Data Science, and Deep Learning with Python

Welcome to the course!

You’re about to learn some highly valuable knowledge, and mess around with a wide variety of data science and machine learning algorithms right on your own desktop! But first, you need to install some stuff.

1. Get the Course Materials

Download all of the scripts and sample data used in this course from this link:

http://media.sundog-soft.com/ml/MLCourse.zip

After downloading, decompress this zip file into a folder in a place you’ll remember. On Windows, you can right-click and select “expand all” after moving the file where you want it to go. Linux users may use the “unzip” command, and on MacOS you may need to install a separate utility to decompress ZIP archives.

If you want a copy of the slides for this course, you’ll find them at http://media.sundog-soft.com/ml/MLCourseSlides.pdf .

(We have discontinued our Facebook group due to abuse.)

2. Install Anaconda, or Use our Hosted Environment

NEW! We now offer a hosted Jupyter notebook environment with all of this course’s activities and exercises pre-loaded for you! Head to https://nimblebox.ai/sundog-education.html to sign up. This is a third party service that involves additional fees, and it is entirely optional. But, it will save you the hassle of installing Anaconda on your own PC, or allow you to go hands-on if you don’t have access to a PC. It also provides you with a hands-on development environment you can use for your own practice and experimentation going forward, even when you’re done with the course.

If you prefer to run things locally on your own for free, you can still do that instead. Just follow these instructions:

This course requires a scientific Python 3 installation that includes Jupyter notebook support. I use Anaconda; here’s how to get set up:

Download and install Anaconda (it’s free) at

https://www.anaconda.com/distribution/

Be sure to select a Python 3 version.

Once installed, open an Anaconda command prompt, and install Tensorflow and pydotplus:

pip install tensorflow 

conda install pydotplus

That’s it! To see if it works, let’s try opening up one of the notebooks included in the course. Let’s assume you saved your course materials into the E:\MLCourse directory; we need to launch Jupyter Notebook from the same directory you saved the notebooks to:

E:\
cd E:\MLCourse
jupyter notebook

And now, you should be able to select a notebook and run it.

Optional: Join Our List

Join our low-frequency mailing list to stay informed on new courses and promotions from Sundog Education. As a thank you, we’ll send you a free course on Deep Learning and Neural Networks with Python, and discounts on all of Sundog Education’s other courses! Just click the button to get started.

Optional: Get the Book

A printed companion book is available from Packt Publishing! It’s a great reference to accompany the course, or a way to follow along when you’re not in front of a computer. Check it out at Amazon.