Getting Started with ML
Setup
- Install Python 3.6+ (
brew install python
for macs) - Install pip with
curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py
- Install pipenv (
brew install pipenv
on mac, otherwisepip install pipenv
) - Clone this repo and run
pipenv install
to install dependencies - Run
pipenv shell
to start virtual environment - Run
jupyter notebook
to start Jupyter server
We will mostly work from Jupyter notebooks so you won't need an IDE. But if you wish to do more serious Python developement, then download PyCharm. The free community edition includes everything you need.
Schedule
Week 1: Intro to Classification
- How classify images
- HW: watch fast.ai lesson 1
Week 2: Image Classification with Convolutional Neural Networks
- How to classify images with CNNs
- HW: build a Simpsons characters classifier
Week 3: Advanced Techniques in Image Classification
- Building better CNNs
- HW: watch fast.ai lesson 2
- HW: build a fruit classifier
Week 4: Gradient Descent Deep Dive
- Optimization 201
- HW: implement gradient descent in Python
- HW: watch fast.ai lesson 3
Week 5: Regression
- Linear, polynomial, and logistic regression
- Feature engineering 101