/ml_studygroup

Primary LanguageJupyter Notebook

Getting Started with ML

Setup

  1. Install Python 3.6+ (brew install python for macs)
  2. Install pip with curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py
  3. Install pipenv (brew install pipenv on mac, otherwise pip install pipenv)
  4. Clone this repo and run pipenv install to install dependencies
  5. Run pipenv shell to start virtual environment
  6. 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