Publications by Business Science
tidyquant v1.0.0: Pivot Tables, VLOOKUPs in R
I’m pleased to announce the release of tidyquant version 1.0.0 that includes Excel in R (Pivot Tables, VLOOKUPs, Sum-Ifs, and 100+ Excel Functions). I’ve also integrated the FREE Tiingo API via riingo. There are a ton of new features that are covered in my ‘R for Excel Users Tutorial’ on Business Science_. Highlights: tidyquant 1.0.0 Th...
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R Shiny vs Tableau (3 Business Application Examples)
Shiny, a web framework that is written in R, often gets lumped into the conversation with Tableau and PowerBI – two popular Business Intelligence (BI Tools) used for “Dashboarding”. The critical point is that Shiny is much more than just a dashboarding tool: R and Shiny combine both machine learning and decision-making, packaging your data ...
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Time Series Machine Learning (and Feature Engineering) in R
Machine learning is a powerful way to analyze Time Series. With innovations in the tidyverse modeling infrastructure (tidymodels), we now have a common set of packages to perform machine learning in R. These packages include parsnip, recipes, tune, and workflows. But what about Machine Learning with Time Series Data? The key is Feature Engineerin...
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3 Free Resources to Learn R – Now Open
The coronavirus (COVID-19) is changing our living and working lives. Social distancing is the new norm for many, and each country is dealing with this situation differently. But, we are all in this together and we will get through this together. I want you to know that during this challenging time, Business Science is offering free educational re...
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How to Run Python’s Scikit-Learn in R in 5 minutes
The 2 most popular data science languages – Python and R – are often pitted as rivals. This couldn’t be further from the truth. Data scientists that learn to use the strengths of both languages are valuable because they have NO LIMITS. Machine Learning: They can switch to Python to leverage scikit learn and tensorflow. Data Wrangling, Visu...
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How to Set Up TensorFlow 2 in R in 5 Minutes (BONUS Image Recognition Tutorial)
The 2 most popular data science languages – Python and R – are often pitted as rivals. This couldn’t be further from the truth. Data scientists that learn to use the strengths of both languages are valuable because they have NO LIMITS. Machine Learning and Deep Learning: They can switch to Python to leverage scikit learn and tensorflow. Da...
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(JUST RELEASED) timetk 2.0.0: Visualize Time Series Data in 1-Line of Code
I’m EXTACTIC ???? to announce the release of timetk version 2.0.0. This is a monumental release that significantly expands the functionality of timetk to go WAY BEYOND the original goals of the package. Now, the package is a full-featured time series visualization, data wrangling, and preprocessing toolkit. I’ll go into detail about what you ...
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Time Series in 5-Minutes, Part 1: Visualization with the Time Plot
Have 5-minutes? Then let’s learn time series. In this short articles series, I highlight how you can get up to speed quickly on important aspects of time series analysis. Today we are focusing on the most fundamental tool, the time plot. Learn how to make interactive (plotly) and static (ggplot2) visualizations easily with timetk. Updates This ...
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Time Series in 5-Minutes, Part 2: Autocorrelation and Cross Correlation
Have 5-minutes? Then let’s learn time series. In this short articles series, I highlight how you can get up to speed quickly on important aspects of time series analysis. Today we are focusing on a critical visualization technique: Autocorrelation and Cross Correlation. Learn how to make interactive (plotly) and static (ggplot2) visualizations ...
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Introducing Modeltime: Tidy Time Series Forecasting using Tidymodels
I’m beyond excited to introduce modeltime, a new time series forecasting package designed to speed up model evaluation, selection, and forecasting. modeltime does this by integrating the tidymodels machine learning ecosystem of packages into a streamlined workflow for tidyverse forecasting. Follow this article to get started with modeltime. If ...
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