It is interesting that we can find flux topology example for HBase and Kafka but it’s hard to find one for Redis.

This task is verified on top of Hadoop 3.1.1. Work as user “hadoop” if not specified.

Given an input file which is an attributes list of one place. The attributes of the place consists of a number of category instances. Each line represents one place. Examples are as following:

With Hortonworks Sandbox 2.6 we’ll have a brief exercise using Pig to take a look at movie dataset.

This shiny application is deployed to Rstudio shiny server. Here is the app link. And Source code link

We’ll start with downloading the text data from SwiftKey link . The data includes blogs, news and twitters text files. They are available in multiple languages but We’ll only deal with the data files in English. Then I’ll analyze the data using text mining and NLP approaches to discover the structure in the data and how words are put together. After that, I’ll be building a predictive text model to predict the most likely next word. Finally, I’ll create a data product using shiny app (covered in part 2).

This project was capstone project for Coursera Data Science Specialization held by Johns Hopkins University. SwiftKey is corporate partner in this project.

This project assumes that you work for Motor Trend, a magazine about the automobile industry. Looking at a data set (mtcars from datasets library) of a collection of cars, they are interested in exploring the relationship between a set of variables and miles per gallon (MPG) (outcome). They are particularly interested in the following two questions:

The requirements to this assignment in DS course by JHU:

1. Create a web page using R Markdown that features a map created with Leaflet.
2. Host your webpage on either GitHub Pages, RPubs, or NeoCities.
3. Your webpage must contain the date that you created the document, and it must contain a map created with Leaflet.

This project is a final project for Data Viz course by UIUC in Coursera. The purpose of the project is to practice narrative visualization structure using Java script plus Vega/Vega-lite libraries.

Storms and other severe weather events can cause both public health and economic problems for communities and municipalities. Many severe events can result in fatalities, injuries, and property damage, and preventing such outcomes to the extent possible is a key concern.

In this simple note, I will investigate the exponential distribution in R and compare it with the Central Limit Theorem(CLT). CLT tells us that sample mean distribution is a normal distribution when sample size is large enough (for example >30). Expected value of sample mean distribution is used to estimate population mean. Sample mean variance is population variance divided by sample size.

So when talking about data models in the context of data curation, we know there are three main types: relational model, tree model and Entity-Relationship (ER) model.

Looking back for all the studies in past year, here comes a high level understanding/summary to the Data Science process - where how far we’ve gone and we’ll start in next year.

This is an assignment in Coursera Big Data course by UCSD.

This is an assignment in Coursera Big Data course by UCSD.

A lot has had happened in past one year.