A visual exploration of the 2017-2018 NBA landscape The modern NBA landscape is rapidly changing. Steph Curry has redefined the lead guard prototype with jaw-dropping shooting range coupled with unprecedented scoring efficiency for a guard. The likes of Marc Gasol, Al Horford and Kristaps Porzingis are paving the way for …
Many types of machine learning classifiers, not least commonly-used techniques like ensemble models and neural networks, are notoriously difficult to interpret. If the model produces a surprising label for any given case, it's difficult to answer the question, "why that label, and not one of the others?". One approach to …
In this post, we give you a quick overview of what we've released recently, and what's coming up.
In this post, we use linear regression in R to build a model that predicts cherry tree volume.
This Domino Data Science Field Note blog post provides highlights of Hadley Wickham’s ACM Chicago talk, “You Can’t Do Data Science in a GUI”. In his talk, Wickham advocates that, unlike a GUI, using code provides reproducibility, data provenance, and the ability to track changes so that data scientists have …
The dplyr package in R is a powerful tool to do data munging and manipulation, perhaps more so than many people would initially realize. Shortly after I embarked on the data science journey earlier this year, I came to increasingly appreciate the handy utilities of dplyr
Jan. 22, 2018, 10:01 p.m.
The dplyr package in R is a powerful tool to do data munging and manipulation, perhaps more so than many people would initially realize. Shortly after I embarked on the data science journey earlier this year, I came to increasingly appreciate the handy utilities of dplyr
Jan. 22, 2018, 10:01 p.m.
Reading Time: < 1 minute15 Min Read The post dplyr : Data Manipulation and Exploration: The Curious Oenophile appeared first on Data Science Blog.
Jan. 22, 2018, 10:01 p.m.
For someone like me, who has only some programming experience in Python, the syntax of R programming felt alienating, initially. However, I believe it’s just a matter of time before you adapt..
For someone like me, who has only some programming experience in Python, the syntax of R programming felt alienating, initially. However, I believe it’s just a matter of time before you adapt..
Reading Time: 1 minute25 Min Read The post An Introduction to R Programming appeared first on Data Science Blog.
Last week we ran a Data Science survey asking four simple questions to our community. In this post, I’ll show you the results of our survey and provide you with a Jupyter notebook; just in case you want to play with the data yourself. Disclaimer 2,233 people participated in the …
Oct. 27, 2017, 10:29 p.m.
In this first episode of "Season 2" of Becoming a Data Scientist podcast, we meet Jasmine Dumas, a new data scientist who tells us about going from biomedical engineering into a data science project experience and then finding her first job as a data scientist. Podcast Audio Links: Link to …
In this episode, Renee interviews Bioinformatics PhD and Data Scientist Erin Shellman about her path to becoming a data scientist, including jobs at Nordstrom Innovation Lab and zymergen. Erin discusses school, job interviews, teaching, and eventually getting to do data science within her field of scientific expertise. Podcast Audio Links: …
For anyone that hasn’t yet joined the Becoming a Data Scientist Podcast Data Science Learning Club, I thought I’d write up a summary of what we’ve been doing....
In August 2014, I created a 40-minute video tutorial introducing the key functionality of the dplyr package in R. dplyr continues to be my "go-to" package for data exploration and manipulation because of its intuitive syntax, blazing fast performance, and excellent documentation. I recorded that tutorial using the latest version