Welcome and Logistics
  • Introduction and Outline
  • What will you learn in this course?
  • What level of machine learning is taught in this course?
  • How will you practice what you learned in this course?
  • Extra Resources
Numpy (New)
  • Numpy Section Introduction
  • Arrays vs Lists
  • Dot Product
  • Speed Test
  • Matrices
  • Solving Linear Systems
  • Generating Data
  • Numpy Exercise
  • Where to Learn More Numpy
  • Suggestion Box
Matplotlib (New)
  • Matplotlib Section Introduction
  • Line Chart
  • Scatterplot
  • Histogram
  • Plotting Images
  • Matplotlib Exercise
  • Where to Learn More Matplotlib
Pandas (New)
  • Pandas Section Introduction
  • Loading in Data
  • Selecting Rows and Columns
  • The apply() Function
  • Plotting with Pandas
  • Pandas Exercise
  • Where to Learn More Pandas
Scipy (New)
  • Scipy Section Introduction
  • PDF and CDF
  • Convolution
  • Scipy Exercise
  • Where to Learn More Scipy
Bonus Exercises
  • More Exercises
Beginner Troubleshooting
  • What if I don't meet the math prerequisites?
Machine Learning Basics
  • Machine Learning: Section Introduction
  • What is Classification?
  • Classification in Code
  • What is Regression?
  • Regression in Code
  • What is a Feature Vector
  • Machine Learning is Nothing but Geometry
  • All Data is the Same
  • Comparing Different Machine Learning Models
  • Machine Learning and Deep Learning: Future Topics
  • Machine Learning Section Summary
Setting Up Your Environment (FAQ by Student Request)
  • Pre-Installation Check
  • Anaconda Environment Setup
  • How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow
Extra Help With Python Coding for Beginners (FAQ by Student Request)
  • Python 2 vs Python 3
  • Proof that using Jupyter Notebook is the same as not using it
Effective Learning Strategies for Machine Learning (FAQ by Student Request)
  • Machine Learning and AI Prerequisite Roadmap (pt 1)
  • Machine Learning and AI Prerequisite Roadmap (pt 2)
Appendix / FAQ Finale