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Name: fjgirante

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DataCamp Template Course

This an automatically generated DataCamp course. Use it as a reference to create your own interactive course.

Changes you make to this GitHub repository are automatically reflected in the linked DataCamp course. This means that you can enjoy all the advantages of version control, collaboration, issue handling ... of GitHub.

Workflow

Edit the markdown and yml files in this repository. You can use GitHub's online editor or use git locally and push your changes.
Check out your build attempts on the Teach Dashboard.
Check out your automatically updated course on DataCamp

Getting Started

A DataCamp course consists of two types of files:

course.yml, a YAML-formatted file that's prepopulated with some general course information.
chapterX.Rmd, a markdown file with:
- a YAML header containing chapter information.
- markdown chunks representing DataCamp Exercises.

To learn more about the structure of a DataCamp course, check out the documentation.

Every DataCamp exercise consists of different parts, read up about them here. A very important part about DataCamp exercises is to provide automated personalized feedback to students. In R, these so-called Submission Correctness Tests (SCTs) are written with the testwhat package. SCTs for Python exercises are coded up with pythonwhat. Check out the GitHub repositories' wiki pages for more information and examples.

Want to learn more?

Check out the DataCamp Teach documentation.
Check out DataCamp's blog posts:
- Create a course with DataCamp Teach
- Interpreting DataCamp Teach's build attempts.

Happy teaching!

fjgirante's Projects

2015

Public material for CS109

awesome-datascience

:memo: An awesome Data Science repository to learn and apply for real world problems.

awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

data-analysis-and-machine-learning-projects

Repository of teaching materials, code, and data for my data analysis and machine learning projects.

data-science-45min-intros

Ipython notebook presentations for getting starting with basic programming, statistics and machine learning techniques

data.table

R's data.table package extends data.frame. HOMEPAGE:

datascienceresources

Open Source Data Science Resources.

ds

fjgirante

free-data-science-books

Free resources for learning data science

go

The Open Source Data Science Masters

learndatascience

Open Content for self-directed learning in data science

notebooks

Some sample IPython notebooks for scikit-learn

open-data-contract-standard

Home of the Open Data Contract Standard (ODCS).

pattern_classification

A collection of tutorials and examples for solving and understanding machine learning and pattern classification tasks

python-raindropio

Python wrapper for Raindrop.io API.

rss2pocket

An awesome tool to save articles from RSS feed to Pocket automatically.

scikit-learn

scikit-learn: machine learning in Python

scikit-learn-tutorial

Applied Machine Learning in Python with scikit-learn

sklearn_pandas_tutorial

EuroScipy 2014 tutorial: Introduction to predictive analytics with pandas and scikit-learn

sklearn_tutorial

Slides for quick intro to machine learning with sklearn

slu05

SLU05 - Git Intermediate: Exercise 4: Git remotes

test

1

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