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Data Science Tutorials

Develop your data science skills with tutorials in our blog. We cover everything from intricate data visualizations in Tableau to version control features in Git.
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Deep Learning

Deep Learning with Jupyter Notebooks in the Cloud

This step-by-step tutorial will show you how to set up and use Jupyter Notebook on Amazon Web Services (AWS) EC2 GPU for deep learning.

Dan Becker

March 23, 2017

Python

Python Dictionary Tutorial

In this Python tutorial, you'll learn how to create a dictionary, load data in it, filter, get and sort the values, and perform other dictionary operations.
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DataCamp Team

February 16, 2017

Python

Scipy Tutorial: Vectors and Arrays (Linear Algebra)

A SciPy tutorial in which you'll learn the basics of linear algebra that you need for machine learning in Python, with a focus how to with NumPy.
Karlijn Willems's photo

Karlijn Willems

February 8, 2017

R Programming

Web Scraping and Parsing Data in R | Exploring H-1b Data Pt. 1

Learn how to scrape data from the web, preprocess it and perform a basic exploratory data analysis with R
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Ted Kwartler

January 12, 2017

R Programming

15 Easy Solutions To Your Data Frame Problems In R

Discover how to create a data frame in R, change column and row names, access values, attach data frames, apply functions and much more.
Karlijn Willems's photo

Karlijn Willems

January 10, 2017

Python

Preprocessing in Data Science (Part 3): Scaling Synthesized Data

You can preprocess the heck out of your data but the proof is in the pudding: how well does your model then perform?
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Hugo Bowne-Anderson

May 10, 2016

Python

Preprocessing in Data Science (Part 1): Centering, Scaling, and KNN

This article will explain the importance of preprocessing in the machine learning pipeline by examining how centering and scaling can improve model performance.
Hugo Bowne-Anderson's photo

Hugo Bowne-Anderson

April 26, 2016

Data Science

The Data Science Industry: Who Does What (Infographic)

This infograph compares the roles of data scientists, data analysts, data architects, data engineers and more in the data science industry.
Karlijn Willems's photo

Karlijn Willems

November 10, 2015