Blog Archives

Using MongoDB with R

March 2, 2017
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Using MongoDB with R

MongoDB is a NoSQL database program which uses JSON-like documents with schemas. It is free and open-source cross-platform database. MongoDB, top NoSQL database engine in use today, could be a good data storage alternative when analyzing large volume data. To use MongoDB with R, first, we have to download and install MongoDB Next, start MongoDB. Related Post

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Using PostgreSQL and shiny with a dynamic leaflet map: monitoring trash cans

March 1, 2017
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Using PostgreSQL and shiny with a dynamic leaflet map: monitoring trash cans

When there is increased social activity, trash cans can get full quicker. On the contrary, during very cold weather, trash cans can take one or a couple of more days to get full. Therefore, knowing when trash cans are full is important to pick them up right away rather than waiting for a specific day PostgreSQL and shiny...

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Logistic Regression Regularized with Optimization

February 25, 2017
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Logistic Regression Regularized with Optimization

Logistic regression predicts the probability of the outcome being true. In this exercise, we will implement a logistic regression and apply it to two different data sets. The file ex2data1.txt contains the dataset for the first part of the exercise and ex2data2.txt is data that we will use in the second part of the exercise. Related Post

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Analytical and Numerical Solutions to Linear Regression Problems

February 18, 2017
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Analytical and Numerical Solutions to Linear Regression Problems

This exercise focuses on linear regression with both analytical (normal equation) and numerical (gradient descent) methods. We will start with linear regression with one variable. From this part of the exercise, we will create plots that help to visualize how gradient descent gets the coefficient of the predictor and the intercept. In the second part, Related Post

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Visualizing Streaming Data And Alert Notification with Shiny

February 13, 2017
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Visualizing Streaming Data And Alert Notification with Shiny

Streaming Data is data that is generated continuously and it includes various sources such as sensors, log files, geospatial services, etc. The data may come at regular intervals and we may want to have a dashboard which updates by itself and incorporates the newly added data so that we can use it for deta driven Email and Text...

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Machine Learning for Drug Adverse Event Discovery

September 26, 2016
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Machine Learning for Drug Adverse Event Discovery

We can use unsupervised machine learning to identify which drugs are associated with which adverse events. Specifically, machine learning can help us to create clusters based on gender, age, outcome of adverse event, route drug was administered, purpose the drug was used for, body mass index, etc. This can help for quickly discovering hidden associations Related Post

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The importance of Data Visualization

September 2, 2016
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The importance of Data Visualization

Before we perform any analysis and come up with any assumptions about the distributions of and relationships between variables in our datasets, it is always a good idea to visualize our data in order to understand their properties and identify appropriate analytics techniques. In this post, let’s see the dramatic differences in conclutions that we Related Post

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Best packages for data manipulation in R

May 17, 2016
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Best packages for data manipulation in R

There are 2 packages that make data manipulation in R fun. These are dplyr and data.table. Both packages have their strengths. While dplyr is more elegant and resembles natural language, data.table is succinct and we can do a lot with data.table in just a single line. Further, data.table is, in some cases, faster (see benchmark Related Post

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Working with databases in R

April 2, 2016
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Working with databases in R

The dplyr package, which is one of my favorite R packages, works with in-memory data and with data stored in databases. In this extensive and comprehensive post, I will share my experience on using dplyr to work with databases. The basic functions of dplyr package are covered by Teja in another post at DataScience+ Using Related Post

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Performing SQL selects on R data frames

March 13, 2016
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Performing SQL selects on R data frames

For anyone who has SQL background and who wants to learn R, I guess the sqldf package is very useful because it enables us to use SQL commands in R. One who has basic SQL skills can manipulate data frames in R using their SQL skills. You can read more about sqldf package from cran. Related Post

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