End-to-End Machine Learning Library

Welcome! Pour yourself a mug of something hot and have a look around.

If you're wondering where to get started, here are some recommended course sequences. Whether you are new to data science or want to dive into building your own neural networks, there is a set of courses lined up for you.

300 series. Project courses with coding.

September 1, 2020

316. Recurrent Neural Networks

June 1, 2020

315. Convolutional Neural Networks

neural network optimization course

314. Neural Network Optimization

  • Build an autoencoder to extract basis elements of images of the Martian surface.
  • Optimize compression performance by tuning hyperparameters.
  • Build and use Evolutionary Powell's method, an experimental hyperparameter optimization algorithm.
advanced neural network methods course

313. Advanced Neural Network Methods

neural network visualization course

312. Build a Neural Network Framework

  • Code up a fully connected deep neural network from scratch in Python.
  • Extend it into a framework through object-oriented design.
neural network visualization course

311. Neural Network Visualization

  • Create a custom neural network visualization in python.
  • Learn Matplotlib tricks for making professional plots.

200 series. Application-centered case studies.

polynomial regression course

213. Polynomial Regression

  • Code up a robust optimizer from scratch in python.
  • Fit high-order polynomials to real data on dog breeds.
  • Implement Monte Carlo cross-validation to select the best model.
time-series course

212. Time-series Prediction

  • Build a command line weather prediction tool from a century of data.
  • Perform data-driven deseasonalization to remove annual weather patterns.
  • Use autocorrelation to extract predicted temperatures.
decision trees course

211. Decision Trees

  • Code up a decision tree in python from scratch.
  • Dynamically construct URL queries for live transit data API.
  • Use Pandas DataFrames to model transit time distributions.
  • Build the model into a command line application.

100 series. Foundational concepts and skills.

Everything below this line is free.

how neural networks work course

193. How Neural Networks Work

how stuff works course

191. How Selected Models and Methods Work

how optimization works course

173. How Optimization for Machine Learning Works

model selection course

171. How to Choose a Model

matplotlib course

133. How to Navigate Matplotlib

data munging course

131. Data Munging Tips and Tricks

data science career advice

121. Navigating a data science career

data science concepts

101. Data science concepts

Foundational Skills