johnny-alpha Goto Github PK

cortana-intelligence-predictive-maintenance-aerospace

Predict the remaining useful life of aircraft components in order to reduce component repair costs, improve component stock availability, reduce inventory levels of related assets and improve maintenance planning.

creating-maps-in-r

Introductory tutorial on graphical display of geographical information in R.

datasharing

The Leek group guide to data sharing

discountfactorcalculator

Calculate discount factors from deposit rates. Very basic

exdata_plotting1

Plotting Assignment 1 for Exploratory Data Analysis

finitedifferencemethod

Round 2 of the C++ code

fsharprprovider

An F# Type Provider to interop with R

gettingandcleaningdata

This is a repo for the Coursera course of the same title. see https://class.coursera.org/getdata-006 for more details

machinelearningan

mxnet-notebooks

Notebooks for MXNet

practical-machine-learning

Welcome to Practical Machine Learning! This course will focus on developing the tools and techniques for understanding, building, and testing prediction functions. These tools are at the center of the Data Science revolution. Many researchers, companies, and governmental organizations would like to use the cheap and abundant data they are collecting to predict what customers will like, what services to offer, or how to improve people's lives. The emphasis of this course is hands on learning and implementation. If you like what you learn in this class, there are a large number of other Machine and Statistical Learning MOOCs that you can use to deepen your knowledge of the technical and mathematical details. Please see the course syllabus for information about the quizes, the project, due dates, and grading. Don't forget to say hi on the message boards. The community developed around these courses is one of the best places to learn and the best things about taking a MOOC!

programmingassignment2

Repository for Programming Assignment 2 for R Programming on Coursera

pythondatasciencehandbook

Code Examples associated with "Python Data Science Handbook" by Jake VanderPlas and published by O'Reilly

pythonmarketenvironment

Creating a market environment to price options and run simulations as a base for the reinforcement learning code to come later

tensorflow

Computation using data flow graphs for scalable machine learning

tensorflow-deepq

A deep Q learning demonstration using Google Tensorflow

tensorflow-docker-template

Dockerfile and project config settings for ensuring a TensorFlow project can execute on the CPU or GPU via docker or nvidia-docker.