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2015-slides

Slides and talk assets from PyCon 2015

2015lab4

Lab for Linear and Logistic Regression, SciKit Learn

2016-afec-x-r-data-visualization

advanced-shiny

Shiny tips & tricks for improving your apps and solving common problems

agoro-field-boundary-detector

Detect field boundaries using satellite imagery.

arcgis-runtime-samples-dotnet

Samples for the ArcGIS Runtime SDK for .NET - Desktop, Store, and Phone

arset23

awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

awesome-rnn

Recurrent Neural Network - A curated list of resources dedicated to RNN

awesome-satellite-imagery-datasets

List of satellite imagery datasets with annotations for computer vision and deep learning

boto3

AWS SDK for Python

caffe-tensorflow

Caffe models in TensorFlow

caffe_scripts

china-cities-air-quality

Air quality data (PM2.5) from different sources

cleaning-titanic-data

One of the most popular starter data sets in data science, the Titanic data set. This is a data set that records various attributes of passengers on the Titanic, including who survived and who didn’t. Here I have detected some missing value, replace the missing values and also create new values added to the dataset. There are two csv files, first one is titanic_original.csv and second one is tatanic_clean.csv. Second csv is generated from the R code, called 'titanic.r' here. Have fun.

connected-nx-tutorial

Repository for code and notebooks for the a NetworkX Tutorial

courses

fast.ai Courses

covid19-healthsystemcapacity

Open geospatial work to support health systems' capacity (providers, supplies, ventilators, beds, meds) to effectively care for rapidly growing COVID19 patient needs

crime_analysis

Crime analysis in R

d3

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

data-visualization-of-global-zika-virus-epidemic-in-2015-and-2016

data-visulization-of-washington-dc-capital-bikesharing

More a complete blog explain the data and results please see: https://geoyi.org/2016/08/19/data-driven%E2%80%8B-city-planning-using-linear-regress-to-predict-bike-sharing-demands-in-washington-dc-%E6%95%B0%E5%AD%97%E5%8C%96%E5%9F%8E%E5%B8%82%E8%AE%A1%E5%88%92%EF%BC%9A%E5%A4%9A%E5%85%83/

dataviz-with-python-and-js

The accompanying files for the book 'Dataviz with Python and JavaScript'

decode

Python code for the DECODE method and mxnet code for Fractal ResUNet

deep-learning-in-production

In this repository, I will share some useful notes and references about deploying deep learning-based models in production.

deep-learning-resource

deeplab_v3

Implementation of the Semantic Segmentation DeepLab_V3 CNN as described in: https://arxiv.org/pdf/1606.00915.pdf

deeplearning-cats-dogs-tutorial

Source code for blog post: A Practical Introduction to Deep Learning with Caffe and Python

deeplearningcoursecodes

deeplearningsandbox

Blog related code for