Data Science using the Julia Language¶

Are you a Data Scientist?

(Or just interested in learning more about data science?)

Are you a Python user? Do you think it's the Bee's Knees?

Well you should give Julia a try and be blown away by its features and speed

Outline¶

This presentation gives a gentle introduction to Julia ith enough hands-on experience in Julia to start applying it to their own projects, or use Julia as a teaching tool in the classroom.

  1. Gentle introduction to the Julia language
  2. Accessing and manipulating data
  3. Exploring data using statistics and data visualization
  4. Automatic differentiation and machine learning algorithms

A Gentle Introduction to Julia¶

  1. Getting Started: Slides Notebook
  2. The structure of a Julia Program (modules, control flow, and functions): Slides Notebook
  3. Methods, and Introspection: Slides Notebook
  4. Structured Data Types (Classes): Slides Notebook

Explore on GitHub

Accessing and Manipulating Data¶

  1. Array-Based Data Types Slides Notebook
  2. File I/O Slides Notebook
  3. Database I/O Slides Notebook

Explore on GitHub

Exploring Data using Statistics and Data Visualization¶

  1. Plotting Slides Notebook
  2. Statistics Slides Notebook
  3. Interact.jl Slides Notebook

Explore on GitHub

More things to look at:

  1. KernelDensityEstimate.jl
  2. OnlineStats.jl

Exploring Automatic Differentiation and Machine Learning Algorithms¶

  1. Automatic Differentiation: Slides Notebook
  2. Deep learning with Flux.jl Slides Notebook

Explore on GitHub

More things to look at:

  1. SciML.ai
  2. Using Flux with CUDA: https://fluxml.ai/Flux.jl/stable/gpu/