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This course curriculum is designed with the objective of enabling beginner level programmers in getting up to speed with Julia
Data, Methods, and Visualizations for Data Science in Julia
A course for people who are hesitant but curious about learning to write code in Julia.
Learn about how to do computational modeling in the Julia programming language with applications focused on the COVID-19 Pandemic.
Syllabus: Motivation; Representing Data with Models; Building Models; Model Complexity; What is Learning?; What are Neurons?; Flux.jl, the Elegant Julia Machine Learning Library ;
In-memory tabular data in Julia: http://juliadata.github.io/DataFrames.jl/stable/
Syllabus: Flux Basics - Why Flux?- Building Deep Learning Models - Intro- Introduction to Flux (21:16) Using Flux - Introduction to Neural Networks (16:58)- Deep Learning with Flux (29:41)- Recognizing handwriting with a neural network (27:37)
Syllabus: Introduction - Introduction (10:24)- Performance Overview (27:16) Optimizing Single-Core Performance - Serial Performance (43:49)- Single Instruction, Multiple Data (27:36) Parallel Strategies - Multithreading (52:04)- Parallel Algorithm Desi…
Syllabus: Welcome to the world of Machine Learning - Introduction- Visual Question and Answering- Handwriting Recognition in Julia- Sentiment Analysis- Language Modeling- Image Classification
How to build and solve decision making problems using the POMDPs.jl ecosystem of packages
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