gmineo

gmineo's Stars

• d3/d3

  Bring data to life with SVG, Canvas and HTML. :bar_chart::chart_with_upwards_trend::tada:

  Language:Shell109k22.9k

• facebookresearch/Detectron

  FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

  Language:Python26.3k5.5k

• facebookresearch/maskrcnn-benchmark

  Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.

  Language:Python9.3k2.5k

• datasets/exchange-rates-usd

  Exchange Rates Data Package

  Language:Python87

• datasets/gold-prices

  Gold prices data package

  Language:Python4340

• datasets/finance-vix

  CBOE Volatility Index (VIX) time-series dataset including daily open, close, high and low.

  Language:Makefile6234

• patrickl086/Fashion_Mnist

  Language:R1

• treselle-systems/loan_prediction_using_PCA_and_naive_bayes_classification_with_R

  Nowadays, there are numerous risks related to bank loans both for the banks and the borrowers, who get the loans. The risk analysis about bank loans needs understanding about the risk and the risk level. Banks need to analyze their customers for loan eligibility so that they can specifically target those customers. Banks wanted to automate the loan eligibility process (real time) based on customer details such as Gender, Marital Status, Age, Occupation, Income, debts and others, provided in their online application form. As the number of transactions in banking sector is rapidly growing and huge data volumes are available, the customers’ behavior can be easily analyzed and the risks around loan can be reduced. So, it is very important to predict the loan type and loan amount based on the banks’ data

  Language:R1218

• amrrs/animated_bar_charts_in_R

  Code to demo how to build Animated Bar Charts in R

  Language:R105119

• thomasp85/gganimate

  A Grammar of Animated Graphics

  Language:R1.9k310

• rafalab/dsbook

  Repository for data science book

  Language:TeX1.1k1.1k

• Borye/machine-learning-coursera-1

  This repo is specially created for all the work done my me as a part of Coursera's Machine Learning Course.

  1.1k909

• jokecamp/jokecamp.com

  personal blog and website

  Language:HTML8340

• bpoweski/practical-machine-learning

  Project for the Coursera "Practical Machine Learning" class

  Language:R117

• rikunert/BTW2017_manifesto_analysis

  a series of analyses of German party manifestos leading up to the 2017 general election

  Language:R1

• AlessandroCorradini/Harvard-Data-Science-Professional

  Repository for the Data Science Professional Program from Harvard University on edX

  Language:HTML3837

• fxcm/MarketData

  MarketData

  Language:Python11638