Welcome to the Machine Learning and AI Study Group
Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI.
(Definition taken from Andrew Ng’s Machine Learning Course)
Study Group Setup
- Resources such as notes, exercises and samples will be uploaded here.
- Our 1.5-2 hours will be divided into:
- Introduction/Getting to know first-timers
- Discuss questions/issues raised on discussion board
- Lightning Talk
- Self-paced or mini study session
- Today I Learned (TIL)
- Announcement
- Check out these useful cheatsheets.
- If you have questions, please feel free to ask and participate in our Official ML/AI Gitter.
Credits
We based our materials and exercises, with permission, on Professor Jennifer Widom’s short course on Big Data.
Our Milestones
Getting started
- Jupyter/Anaconda Installation
- Or, work in the cloud: https://colab.research.google.com
Python for Machine Learning (Crash Course/Review)
- Python Basics Tutorial
- Exercise 1: Datatypes: Numbers, Strings, Booleans
- Exercise 2: Containers: Lists and Dictionaries
- Exercise 3: Functions
- Python Advanced for Data
Basic Data Manipulation with Pandas
- Pandas Basics Tutorial
- Exercise Option 1: Learning Pandas with Pokemon
- Exercise Option 2: Learning Pandas with McDonalds
Basic Data Visualization
Introduction to Machine Learning using Scikit-learn
- Your First Machine Learning Project: Iris Plant Classification
- Exercise: Handwritten Digit Recognition (MNIST)
Basic Regression
Math of Intelligence Series
In-depth discussions of the different machine learning algorithms.
Topic | Slide Set | Samples | Exercise | Resources |
---|---|---|---|---|
Decision Trees | DT Slide Set, Gini Index | DT Example | DT Exercise | DT Video |
Naive Bayes | NB Slide Set | NB Example | NB Exercise | NB Video |