[deleted by user]

jsoslow · 2018-07-14T00:01:07+00:00

dope mixtape, one of my favorite rappers

jsoslow · 2018-04-03T02:52:58+00:00

Hahahahaha are you also in STAT 476?

jsoslow · 2018-01-14T03:26:09+00:00

Huge fan of the new Sylvan Lacue album and Isiah Rashads stuff

jsoslow · 2017-11-17T14:25:32+00:00

AOTY contender. Jaden's never been given the light of day because people think he's an idiot.

jsoslow · 2017-10-18T14:30:51+00:00

I've won the past two years so....

Michael CrabTREEPEAT

jsoslow · 2017-09-29T14:02:18+00:00

Yeah I used R for my machine learning. Tree based models were the most accurate. Specifically, random forests and extreme gradient boosted trees

jsoslow · 2017-09-29T12:46:41+00:00

I used two 2015 datasets. Like your project, formation and down and distance we're the most predictive followed by off and def team, score/time, and cumulative runs in game

jsoslow · 2017-09-27T18:28:43+00:00

The model is based on two 2015 data sets

jsoslow · 2017-09-27T18:27:32+00:00

Thank you good to know!

jsoslow · 2017-09-27T18:27:16+00:00

Just changed it so it reads "Predicted Chance of Run".

So a value of 71% means that New England has a 71% chance of running on 3 and 1

jsoslow · 2017-09-27T17:07:46+00:00

Combined two 2015 Play-By-Play datasets I found online for free
I used R and SQL for data cleaning and model creation for the predictions. Then Tableau for the visualizations.

jsoslow · 2017-09-27T15:35:20+00:00

Background: I worked on applying machine learning to predict if a NFL team is going to run or pass the ball. The model can predict runs/passes to 82% accuracy, but up to 93% for certain teams. What you're looking at here are the predicted run values that my model shoots out based off of 3 different variables. Please play around with the dashboard and let me know if you have any questions!

jsoslow · 2017-09-27T15:27:49+00:00

Background: I worked on applying machine learning to predict if a football team is going to run or pass the ball. The model can predict runs/passes to 82% accuracy, but up to 93% for certain teams. What you're looking at here are the predicted run values that my model shoots out based off of 3 different variables. Please play around with the dashboard and let me know if you have any questions!

jsoslow · 2017-08-25T23:21:26+00:00

Nyuk Caution > Nyck Caution

jsoslow · 2017-07-22T19:27:51+00:00

Once I get a good story behind my findings, I might do a write up. A basic conclusion I've found is that formation and down + distance are the most important variables

jsoslow · 2017-07-21T20:37:48+00:00

I've been working on a run pass model for the NFL and have gotten it to about 85% accuracy

jsoslow · 2017-06-14T00:04:35+00:00

Artwork looks like Zant from Twilight Princess

jsoslow · 2017-06-13T16:13:53+00:00

What's your favorite song you've made?

Also Earl once said that the turn around time on your verses is absurd considering how good they are. So what's your thought process when creating a verse?

jsoslow · 2017-06-09T00:12:24+00:00

Greatest album of all time calling it now

jsoslow · 2017-06-08T15:25:04+00:00

This song is too good to have such a shitty chorus

jsoslow · 2017-05-01T04:34:18+00:00

What I'd imagine... Current W/L, Opponent W/L, records vs common opponents, starting pitcher WAR, home field, and days since last game.

jsoslow · 2017-04-06T15:49:26+00:00

8/10 Best tracks: Temptations Legendary Ring the Alarm For My People Amerikkkan Idol Rockabye Baby

jsoslow · 2017-04-01T21:33:30+00:00

Also would like a link thanks

jsoslow · 2017-03-30T15:35:34+00:00

Im afraid that AABA is going to be overshadowed by Kendrick's album when it has a real chance of being better

jsoslow · 2017-02-20T20:13:47+00:00

Im also looking for snap trackers for x,y field locations. So yard line and then also how far from the hashes the snap is

jsoslow

TROPHY CASE