This article comes from Joon Im, a student in Business Science University. Joon has completed both the 201 (Advanced Machine Learning with H2O) and 102 (Shiny Web Applications) courses. Joon shows off his progress in this Web Scraping Tutorial with rv...
In this tutorial, we’ll show how we used clean_anomalies() from the anomalize package to reduce forecast error by 9%. R Packages Covered: anomalize - Time series anomaly detection Cleaning Anomalies to Reduce Forecast Error by 9% We can often...
This article comes from Jennifer Cooper, a new student in Business Science University. Jennifer is 35% complete with the 101 course - and shows off her progress in this PDF Scraping tutorial. Jennifer has an interest in understanding the plight of wild...
Wrangling Big Data is one of the best features of the R programming language, which boasts a Big Data Ecosystem that contains fast in-memory tools (e.g. data.table) and distributed computational tools (sparklyr). With the NEW dtplyr package, data scien...
I’m pleased to announce the introduction of correlationfunnel version 0.1.0, which officially hit CRAN yesterday. The correlationfunnel package is a tool that enables efficient exploration of data, understanding relationships, and get to business ins...
You’re a Business Analyst - well versed in tools like Tableau, PowerBI, and maybe even SQL, but you want to take your data analytics abilities to the next level, by improving productivity and making predictive business insights with data science (rather than just descriptive insights). Then R is the language for you. In this article, you’ll learn how to...
It continues to amaze us at the progress that our students are making in applying data science in the real world. Bryan Clark (LinkedIn), Data Scientist with H&M and student in our Business Science University DS4B 201-R course has successfully appl...
With the rise of digital marketing led by tools including Google Analytics, Google Adwords, and Facebook Ads, a key competitive advantage for businesses is using A/B testing to determine effects of digital marketing efforts. Why? In short, small change...
Transitioning from Excel to R is one of the best decisions I have ever made. It accelerated my career and it boosted my productivity 10X - 100X (I show how in a Time Study - keep reading). I used Excel primarily for sales and marketing analytics. I was a power-user of Excel fully equipped in VBA, Pivot Tables, Conditional...
The two major data science languages, Python and R, have historically taken two separate paths when it comes to where data scientists are doing the coding. The R language has the RStudio IDE, which is a great IDE for data science because of its feature...
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