- Algorithms In Machine Learning
- Azure Machine Learning Algorithm Cheat Sheet 2017
- Azure Machine Learning Algorithm Cheat Sheet Pdf
Link to Content:
11 Steps for Data Exploration in R
Created/Published/Taught by:
Analytics Vidhya
Content Found Via:
Open Data Science
Free? Yes
Tags: data exploration / R
Algorithms In Machine Learning
Content Type: Cheat Sheets / References, Learning Guides, Etc.Difficulty Rating:
Azure Machine Learning Algorithm Cheat Sheet 2017
Microsoft Azure Machine Learning: Algorithm Cheat SheetMicrosoft Azure's ML cheat sheet is the simplest cheat sheet by far. Even though it's simple, Microsoft was still able to pack a ton of information into it. Azure Machine Learning Studio has a large library of algorithms from the regression, classification, clustering, and anomaly detection families. Each is designed to address a different type of machine learning problem. The Azure Machine Learning Studio Algorithm Cheat Sheet helps you choose the right algorithm for a predictive analytics model.
Azure Machine Learning Algorithm Cheat Sheet Pdf
Azure Machine Learning Algorithm Cheat Sheet; Tip. In any pipeline in the designer, you can get information about a specific module. Select the Learn more link in the module card when hovering on the module in the module list, or in the right pane of the module. Data preparation modules.
“Data Exploration not only uncovers the hidden trends and insights, but also allows you to take the first steps towards building a highly accurate model. Considering the popularity of R Programming and its fervid use in data science, I’ve created a cheat sheet of data exploration stages in R. This cheat sheet is highly recommended for beginners who can perform data exploration faster using these handy codes. All you need to do is, customize the codes according your need.”
This cheat sheet covers the following topics:
- Commonly used R libraries
- How to load a data file
- How to convert a variable to a different data type
- How to transpose a data set
- How to sort a DataFrame
- How to create plots (histogram)
- How to generate frequency tables with R
- How to sample data sets in R
- How to remove duplicate values of a varaible
- How to find class level count average and sum in R
- How to recognize and treat missing values and outliers
- How to merge/join data sets
Recommended Prerequisites: none
Go to Content: Cheatsheet – 11 Steps for Data Exploration in R (with codes)