Getting Started


This workshop series is intended to be fast paced introduction into the theory and applications of Machine Learning. It is assumed that you have a relatively strong basis of Linear Algebra, and Programming to be able to complete this bootcamp.

Just to give an overview of what you will learn (and what you won't learn this time around):

ML Subjects we will cover:

  1. Classical Linear and Clustering ML Algorithms
  2. Deep Learning and Neural Networks
  3. Natural Language Processing Basics
  4. Computer Vision Basics

ML Subjects we won't cover:

  1. Probabilistic Models (Naive Bayes)
  2. Ensemble Models (Random Forest, Adaboost, xgboost)
  3. Reinforcement Learning (Q Learning, Markov Decision Processes)
  4. Deployment of Machine Learning Models


Even though we aren't covering some of the previous topics, there are extra resources and other ML information in the Additional Resources section in the sidebar. Also if you would like workshops on the previous topics, make sure to let us know!



Anaconda makes it very easy to install many tools that are used widely in Machine Learning and Data Science Workflows. It includes many of the Python libraries and tools that we will use in this Bootcamp including but not limited to:

Jupyter Notebook






We will be using Anaconda for the entirety of this bootcamp series for package management

Follow the steps below for your following operating system to install Anaconda.

Jupyter Notebook

Once you have installed Anaconda on your system, launch Jupyter Notebook from Anaconda Navigator.

Jupyter notebook is a program that allows us to run our Python code in our browser in the form of notebooks. These notebooks can include markdown code, display graphs and tables, and run code through cells, meaning you don't have to fully run your code everytime you make an addition. Jupyter notebook may get hard to get used to for the Jupyter novice, but will enable you to be much more productive with your Python code.


Jupyter notebook will open in your computer's base directory, so if you want to open Jupyter notebook in a different folder by default, follow this steps to change your Jupyter default directory: