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bgautijonsson

Brynjolfur Gauti Jónsson

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Tsest case ISLR
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Bylgjur samanburður
Kynning_22Juli
GenLogErindi
GenLogisticResults
LÆK101F: Tidy Data
Neural Networks
Dánartíðni: State Space
Power
Take Home Exam
Final exam for Applied Linear Statistical Models
Fjármálatölfræði: Skil 4
HLT: Verk 5
Fjármálatölfræði: Skil 4
Fyrirlestur
Jaðarreglan
Tölfræði: Lokaverkefni
Áhrifaþættir húsnæðisverðs milli sveitarfélaga á höfuðborgarsvæðinu
Niðurstöður (BS)
BS: Niðurstöður (v2)
Fyrstu niðurstöður
Tölfræði: Lengri Verkefni D
Flokkabreytur
Applied Data Analysis: Report 2
In this report I talk about gradient boosted trees and compare its performance to other linear and tree-based models.
Samantekt um Rannsóknina
Gagnasafn
Prófa ensemble
Plot Hjálp Tölfræði
Data Science Capstone: Presentation
Final Slideshow Presentation for the Capstone Project from John Hopkins University's Data Science Specialization at Coursera.org
ISLR: Exercise 7.8
Exercise 7.8 from Introduction to Statistical Learning
Styttri_verkefni_2
Verkefni_2gagnaskra
Data Science Capstone: Milestone Report
Part of the Capstone Course of the Coursera Data Science Specialization by John Hopkins University
Data Product Presentation
A Study on the Spread of FastFood Restaurants in Reykjavík, Iceland
Hvar er skjaldborgin? Takk, Óli.
R Markdown and Leaflet
The Economic and Population Effects of Different Types of Weather Events
Weather events can have disastrous consequences if we are ill prepared. Heat waves can cause loss of life and floods can cause property damage. If we had reliable information which ranked the different types of events, the government could choose where to spend their budget the most efficiently. The purpose of this analysis is to see which types of events cause the biggest population and property damage. I will look at the mean and total amount of damage caused by major events and plot them for easy viewing.