R Programming

The R programming language is experiencing rapid increases in popularity and wide adoption across industries. This popularity is due, in part, to R’s rich and powerful data visualization capabilities. While tools like Excel, Power BI, and Tableau are often the go-to solutions for data visualizations, none of these tools can compete with R in terms

dplyr is a a great tool to perform data manipulation. It makes your data analysis process a lot more efficient. Even better, it’s fairly simple to learn and start applying immediately to your work! Oftentimes, with just a few elegant lines of code, your data becomes that much easier to dissect and analyze. For these

This presentation will discuss building a business model for your machine learning idea. In this talk, our presenter, Neeti Gupta, will provide a 10-step checklist with examples for the audience to build their own business model. This 10-step business checklist is a synthesis of the speaker’s real world experience evaluating companies that have built a

From distorting experiments with systemic bias to imposing human ethics on machine learning models, data scientists have far more to worry about than the raw numbers in their spreadsheet. Join Raja Iqbal on an exploration of data science’s past evils and how we can pave the way to a brighter future.

According to some estimates, bots constitute close to 50% of the overall traffic. In this introductory talk, we will cover various aspects of feature engineering & detection of automated web traffic. We will start with understanding the impact of bots on an online business and various types of web bots. Finally, we will talk about

In this meetup, I will give a quick introduction to online experimentation and A/B testing. To keep the tutorial self-contained, I will first give an overview of stats fundamentals needed to understand A/B testing. I will explain how A/B testing is done in an online business. In the end, I will mention some of the

Modern machine learning libraries make model building look deceptively easy. An unnecessary emphasis on tools like R, Python, SparkML, and techniques like deep learning is prevalent. Relying on tools and techniques while ignoring the fundamentals is the wrong approach to model building. Real-world machine learning requires hard work, discipline and […]

The R programming language is experiencing rapid increases in popularity and wide adoption across industries. This popularity is due, in part, to R’s rich and powerful data visualization capabilities. While tools like Excel, Power BI, and Tableau are often the go-to solutions for data visualizations, none of these tools can compete with R in terms

Storytelling is a cornerstone of the human experience. Though many elements of stories have remained the same throughout history, we have developed better tools and mediums for telling them, such as printed books, movies, and comics. This has changed storytelling styles—and perhaps most importantly, the impact of those stories. Today the best stories are often

The R programming language is experiencing rapid increases in popularity and wide adoption across industries. This popularity is due, in part, to R’s huge collection of open source machine learning algorithms. If you are a data scientist working with R, the caret package is a must-have tool in your […]

Lecture Starts at: 8:25 Business data presents a challenge for the data analyst. Business data is often aggregated, recorded over time, and tends to exhibit autocorrelation. Additionally, and most problematically, the amount of business data is usually quite limited. These characteristics lead to a situation where many of the tools in the analyst’s tool belt

R programming is rapidly becoming a valuable skill for data professionals of all stripes and a must-have skill for aspiring data scientists. Adding R programming to your data analyst skillset allows you to leverage powerful data visualizations, statistical analyses, and even machine learning in your daily work. In this presentation, Dave Langer illustrates how your

Event logs are everywhere and represent a prime source of Big Data. Event log sources run the gamut from e-commerce web servers to devices participating in globally distributed Internet of Things architectures. Even Enterprise Resource Planning systems produce event logs! Given the rich and varied data contained in event logs, mining these assets […]

Microsoft’s Power BI is a powerful technology for quickly creating rich visualizations. Power BI has many practical uses for the modern data professional including executive dashboards, operational dashboards, and visualizations for data exploration/analysis. Microsoft has also extended Power BI with support for incorporating R visualizations into Power BI projects, enabling a myriad of data visualization

Outline: · Setup a Spark cluster with R installed . · Wrangle data that is inside HDFS using R. · Build and deploy a machine learning model using R. R is currently one of the most popular data science languages in the world. However, it’s always had constraints around scaling out to big data. […]

Nearly 100 years after Einstein predicted the existence of gravitational waves, Laser Interferometer and Gravitational Wave Observatory astounded the world by successfully detecting these waves. Detection was made possible by the advancement of laser technology and data processing techniques. Being able to distinguish the gravitational waves from the background noise was key to verifying […]

At this meetup, presenter Craig Guarraci speaks about how to make sense of unstructured text with Python, MS Cognitive Services & PowerBI. – In this presentation we’ll take a broad look at industry research to see how text analytics and sentiment analysis is used – We’ll look at difficulties associated with sentiment analysis – Review

At this Data Science Dojo meetup, Phuc Duong talks about Building a Real-Time Sentiment Pipeline for Live Tweets Using Python, R, & Azure Supplementary Material found here: https://github.com/gokul180288/meetup…

In this 90-minute talk, we will cover an overview of solving a simple predictive analytics problem. We will use R for feature exploration and visualization and build a predictive model using Azure ML. We will be using the Titanic data set for our exercise. You will see the end-to-end process of building a predictive model.