{"repo":"trenton3983/DataCamp","free":true,"listed":false,"github":"https://github.com/trenton3983/DataCamp","clone":"git clone https://github.com/trenton3983/DataCamp.git","description":"Python-based Jupyter notebooks, notes, and project solutions from DataCamp courses on data science, machine learning, and statistics.","language":"Jupyter Notebook","stars":100,"topics":["data-analysis","data-cleaning","data-science","data-visualization","exploratory-data-analysis","jupyter-notebooks","machine-learning","modeling","numpy","pandas"],"license":null,"category":"machine-learning","readme_excerpt":"DataCamp - DataCamp offers interactive courses in the browser. - I've taken coursers from COURSERA, edX, UDACITY, Udemy and LinkedIn Learning, but I prefer the format implemented by DataCamp. - As noted, the courses are interactive, in the browser, so I have taken the time to create Jupyter Notebooks for most of the courses I've taken. - I have implemented my notebooks in such a way as to be fully executable, though there may be some required backend setup (e.g. downloading data files or setting up a PostgreSQL database). - Links to data are in the notebook. - There are no hidden functions. - An executed HTML version of my notebooks can be found [here][1]. [1]: https://trenton3983.github.io/","default_branch":null,"files":null,"tree":[],"storefront":"/r/trenton3983","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/trenton3983/DataCamp/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}