In the last video, we prepared our dataset for a join. In this video we’ll use the join data module inside of Azure ML to cross reference each airport id with the airport table to find the airport’s city, state and name. We will briefly

In part two of using RStudio for Data Science Dojo’s Kaggle competition, we will show you more advance cleaning functions for your model. This video assumes you have watched part one, if you have not, view it here: https://www.youtube.com/watch?v=Zx2TguRHrJE Titanic Data Set: https://www.kaggle.com/c/titanic Download RStudio:

As part of submitting to Data Science Dojo’s Kaggle competition you need to create a model out of the titanic data set. We will show you how to do this using RStudio. Titanic Data Set: https://www.kaggle.com/c/titanic Download RStudio: https://www.rstudio.com/products/rstudio/download/

Now that Azure Machine Learning Studio is setup, let’s begin an end-to-end data science project in Azure Machine Learning. We’ll choose the flight delay data, and use it to predict whether not a flight will be late on arrival based upon the flight’s circumstances. In

Now that we have a better understanding of our dataset. Let’s go out and gather more data. There is an additional dataset inside of Azure ML we can use to look up and cross reference the airport name with airport id, then bring with it,

Let’s build our first machine learning model in Azure ML. First, we have to go shopping for a machine learning model. We must identify what type of machine learning algorithm we want to choose from. We ended up using a decision tree algorithm because we

What’s better than machine learning? Machine learning where coding is optional! Drag and drop machine learning with a visual interface! We’re going to introduce you to a new tool to add to your data science toolkit, Azure Machine Learning Studio. Azure Machine Learning is a

Today we’ll explore the interface of our new machine learning tool, Azure ML. How do you bring data to and from the outside world into Azure ML? The import dataset module can read in data from a variety of sources: HTTP, Azure SQL database, Hadoop

We introduce you to the wide world of Big Data, throwing back the curtain on the diversity and ubiquity of data science in the modern world. We also give you a bird’s eye view of the subfields of predictive analytics and the pieces of a

In this tutorial we will show you how to complete the titanic Kaggle competition using Microsoft Azure Machine Learning Studio.This video assumes you have an Azure account and you understand how to use Azure. Kaggle Titanic Experiment: https://gallery.cortanaintelligence.com/Experiment/Titanic-Kaggle-Competition-1

The Amazon Web Services Machine Learning platform is finely tuned to enable even the most inexperienced data scientist to build and deploy predictive models in the cloud. In this video, we will walk you through creating an AWS account, uploading data into an S3 bucket,

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

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

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

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

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

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

Web scraping is a very powerful tool to learn for any data professional. With web scraping, the entire internet becomes your database. In this tutorial, we show you how to parse a web page into a data file using a Python package called BeautifulSoup. There

In this full length segment we discuss A/B testing: Online experimentation is perhaps the most misused of data science techniques. We will walk through the best practices for designing and evaluating A/B and multi-variate tests. We discuss how to choose the appropriate metrics, how to

This data science tutorial introduces the viewer to the exciting world of text analytics with R programming. As exemplified by the popularity of blogging and social media, textual data if far from dead – it is increasing exponentially! Not surprisingly, knowledge of text analytics is

This data science tutorial introduces the viewer to the exciting world of text analytics with R programming. As exemplified by the popularity of blogging and social media, textual data if far from dead – it is increasing exponentially! Not surprisingly, knowledge of text analytics is

This data science tutorial introduces the viewer to the exciting world of text analytics with R programming. As exemplified by the popularity of blogging and social media, textual data if far from dead – it is increasing exponentially! Not surprisingly, knowledge of text analytics is

To begin data mining in Azure Machine Learning Studio, we must first setup an Azure subscription. Once we have a subscription, we can create an Azure Machine Learning Studio workspace within Azure. Azure Machine Learning is in the cloud and allows for workspaces to be

This data science tutorial introduces the viewer to the exciting world of text analytics with R programming. As exemplified by the popularity of blogging and social media, textual data if far from dead – it is increasing exponentially! Not surprisingly, knowledge of text analytics is

This is the last video our R series. We finish explaining the basics of data exploration and visualization in R. You should now understand the basics of R and be better prepared to utilize it in bootcamp. Download R: https://cran.r-project.org/ Download RStudio: https://www.rstudio.com/products/rstu…

We introduce plotting packages in the R programming language. Download R: https://cran.r-project.org/ Download RStudio: https://www.rstudio.com/products/rstu…

Continuing with our introduction to the basic features, we show off “apply functions” in the R programming language. Download R: https://cran.r-project.org/ Download RStudio: https://www.rstudio.com/products/rstu…

We introduce the built-in functions for data exploration and alteration. Download R: https://cran.r-project.org/ Download RStudio: https://www.rstudio.com/products/rstu…

We dive deeper into the basics of R and introduce you to the control instructors such as “if statements”. Download R: https://cran.r-project.org/ Download RStudio: https://www.rstudio.com/products/rstu…

Here we introduce the built-in interfaces such as reading and writing text data. Download R: https://cran.r-project.org/ Download RStudio: https://www.rstudio.com/products/rstu…

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 –

Here we show you how to use 3rd party packages for the R programming language. Download R: https://cran.r-project.org/ Download RStudio: https://www.rstudio.com/products/rstu…

Here we explain the missing values of the R programming language, NA, NAN, and NO. R is a free, open-source statistical programming platform. It is designed to make many of the most common data processing tasks as simple as possible. Download R: https://cran.r-project.org/ Download RStudio:

We continue explaining the data functions and types you can use in R. Download R: https://cran.r-project.org/ Download RStudio: https://www.rstudio.com/products/rstu…

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

Here we introduce what lists are in the R programming language. Download R: https://cran.r-project.org/ Download RStudio: https://www.rstudio.com/products/rstu…

Here we introduce data frames in the R programming language. Download R: https://cran.r-project.org/ Download RStudio: https://www.rstudio.com/products/rstu…

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

Here we introduce the basics of matrices in the R programming language. Download R: https://cran.r-project.org/ Download RStudio: https://www.rstudio.com/products/rstu…

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,

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,

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

We introduce you to the wide world of Big Data, throwing back the curtain on the diversity and ubiquity of data science in the modern world. We also give you a bird’s eye view of the subfields of predictive analytics and the pieces of a

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

Part five of data exploration and visualization, we continue our discussion of different visualization techniques to scatter plots and contour plots. This concludes our Data Mining Fundamentals course.

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,

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

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

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

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

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

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

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,

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

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

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

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

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

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

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

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

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 –

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