spurgeondsk

spurgeondsk's Stars

• DataTalksClub/data-engineering-zoomcamp

  Free Data Engineering course!

  Language:Jupyter Notebook25.1k5.4k

• DrakonianMight/NOAA_WW3

  Plot NOAA wave watch 3 data and wave buoy data

  Language:HTML21

• loicduffar/ERA5-tools

  Notebooks Python to download and view ERA5 climatologic data, as well as to extract time series (hourly to monthly data on many atmospheric and land-surface parameters)

  Language:Jupyter Notebook4714

• trondkr/ERA5-ROMS

  Download, and create ERA5 data forcing for ROMS

  Language:Python1713

• ecmwf/notebook-examples

  Example notebooks showing how to work with ECMWF services and data

  Language:Jupyter Notebook19871

• ecmwf/climetlab

  Python package for easy access to weather and climate data

  Language:Python37458

• shamathew/Bin-windspeed-to-wind-direction

  Python code to bin wind speed to wind direction and create rose plot

  Language:Jupyter Notebook3

• tomhopper/windrose

  An R package for creating rose plots from wind data.

  Language:R62

• python-windrose/windrose

  A Python Matplotlib, Numpy library to manage wind data, draw windrose (also known as a polar rose plot), draw probability density function and fit Weibull distribution

  Language:Python338133

• vismethack/challenges

  Language:Jupyter Notebook46

• rstudio/rstudio

  RStudio is an integrated development environment (IDE) for R

  Language:Java4.7k1.1k

• Numer1301/Project-on-Visualizing-Car-Insurance-Claims-using-Tableau

  This project explored the art of problem-solving with the aid of visual analytics. Tableau’s data visualization tools were used to create interactive dashboards to provide high-level insights into an Insurance company to drive the company's car insurance schemes.

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• sebastianmenze/Processing-and-analysis-of-large-ADCP-datasets

  This document will guide you through the steps necessary to process and analyse both vessel mounted (VM-ADCP) and lowered acoustic doppler current profilers (L-ADCP). Both are complex data sources that contain a lot of noise and potential biases, but dont despair, with todays programms and code packages anyone can work with this data and produce meaningfull results.

  Language:MATLAB285

• danoroelvink/shorelines

  ShorelineS free-form coastline simulation program

  Language:WebAssembly3512

• Numer1301/Capstone-Project-on-Insurance-claims

  India is a huge market for insurance but the industry is bleeding losses due to increasing fraud from inside and outside of the system. Insurance frauds leads to close to INR 40,000 crores loss which is close to 8.5% revenue of the insurance sector in India. These huge losses have prompted insurance companies to set-up a new anti-fraud department whose job is to identify the risk and loss to these frauds and to find out ways to reduce fraudulent claims. We now have a data from an insurance company (Name not disclosed) which is losing revenue in fraudulent claims. Based upon the given data build the below models: • Predict if the DRV_CLAIM_STATUS will be 'Rejected' or 'Accepted'. Consider 'Closed' status given in data as 'Accepted' status. This prediction will help the Claims Management team to manage the claims effectively. Prediction model will give them the list of claims to be rejected in advance thus helping them to scrutinize these claims and ensure no leakage in for of frauds. • Identify clusters/associations in the claims data to classify them based on the severity of the claims. Identify fields that are classifying the claims as highly severe claims. These will be the claims that will need more focus and scrutiny from the fraud management team.

  Language:R2