|||

Big Data. Your Commuting Buddy

I used to work in the Transportation field, especially with railroads. Forecasting and recovering from delays was always an tough task because of the ripple effects” that this article mentions, but Mathematician Wilhelm Landerholm figured out an algorithm to forecast delays 2 hours in advance!

Enter big data. Cars on the highway suffer from two problems: there is no monitoring system for tracking their movements and they are operated independently. Commuter train systems, however, do not have these defects. In fact, modern networks have traffic control centers with computer systems keeping track of each train’s location at all times. Ten years ago, this mountain of data would have been unassailable, but with today’s faster machines and this new algorithm it is possible to make accurate predictions about the future state of the train network in a longer time window. It’s a bit like weather forecasting but for your commute. (ed. emphasis mine)

While forecasting these delays is similar to forecasting the weather - and we all know how inaccurate that can be at times - it’s definitely a step in the right direction.

Tl;dr: Big Data is used to forecast transit delays.

Up next Yet Another Language to Learn In today’s Advanced Analytic landscape we often hear about the mythical Data Scientist that can cure all our problems and unearth value hidden deep New RapidMiner Intro Videos I’m pretty excited to have been selected as the “voice of RapidMiner” for 6 new introduction videos that were just posted to YouTube. The first one
Latest posts Revisiting GOOG, GE, NE, IYR from 2007 The Ye Old Blog List Motorola: Then and Now EWM Redux Testing for mean reversion with Python & developing simple VIX system - Talaikis unsorted - Tadas Talaikis Blog Steps to calculate centroids in cluster using K-means clustering algorithm - Data Science Central Basics of Statistical Mean Reversion Testing - QuantStart Algorithmic trading in less than 100 lines of Python code - O’Reilly Media Interpreting Machine Learning Models Microsoft the AI Powerhouse Investing in the S&P500 still beats AI Trading Microsoft makes a push to simplify machine learning | TechCrunch 10 Great Articles On Python Development — Hacker Noon Introduction to Keras Democratising Machine learning with H2O — Towards Data Science Getting started with Python datatable | Kaggle Phone Addiction Machine Learning Making Pesto Tastier 5 Dangerous Things You Should Let Your Kids Do The Pyschology of Writing Investing in 2019 and beyond TensorFlow and High Level APIs Driving Marketing Performance with H2O Driverless AI Machine Learning and Data Munging in H2O Driverless AI with datatable Making AI Happen Without Getting Fired Latest Musings from a Traveling Sales Engineer The Night before H2O World 2019 Why Forex Trading is Frustrating Functional Programming in Python Automatic Feature Engineering with Driverless AI Ray Dalio's Pure Alpha Fund