Here, you’ll find all of ACM AI’s content over the years, including code, blog posts, notes, and slides. Enjoy!

## Spring 2020

### ACM AI Outreach

#### Freely-accesible slides + code + homework assignments covering the following topics:

- What is AI?
- What is ML?
- Plotting data
- Supervised learning framework
- Machine learning math
- Gradient descent
- Linear regression
- Logistic regression
- Bayes’ theorem and normal distribution
- Introduction to fully-connected neural networks
- Optimization and regularization
- Introduction to convolutional neural networks
- AI ethics and self-driving cars
- MNIST classification using CNNs implemented in Keras

#### Conceptual visualization modules

- Gradient descent
- Mean-squared error loss
- Forward propagation in a neural network (coming soon!)

#### Tik Toks

#### “You Belong in AI!” podcast episodes

## Fall 2018

### Beginner Track

#### Workshop #1: Intro to ML

#### Workshop #2: Math and Coding Overview

#### Workshop #3: Linear Regression

#### Workshop #4: Linear Regression: Code

### Advanced Track

#### Workshop #1: ML Review + Neural Networks

#### Workshop #2: Neural Networks

#### Workshop #3: Neural Networks: Code

## Spring 2018

#### Linear Regression

#### Logistic Regression

#### Pandas & Kaggle Hack Session

#### Intro to Neural Networks with Tensorflow

#### More on Neural Networks

#### Convolutional Neural Networks

#### Recurrent Neural Networks with Tensorflow

#### Generative Adversarial Networks

#### Autoencoders

#### Research Paper Reviews

- A few useful things to know about machine learning
- Deep Learning: An overview
- AlexNet, Inception Net, & ResNet notes and slides
- Word2Vec meeting slides