Latex cheat sheet for the EPFL (http://epfl.ch/) course "Pattern Matching and Machine Learning", Fall 2014.

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The parallel cartographic modeling language (PCML) is a multi-institutional collaborative project aiming to create a computing language for cyberGIScientists that is designed for (1) usability, (2) programmability, and (3) scalability.

Summary and cheatsheet for the "Pattern Classification and Machine Learning" class of EPFL's Computer Science Masters with Prof. Emtiyaz Khan

Utilities designed to make working with PCML in JT400 easier.

Map domain objects to IBM's Program Call Markup Language

Pattern Classification and Machine Learning Cheat Sheet for the 2012 Exam. This class is provided in EPFL.

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Generates Java classes from IBM® .PCML-Files (Program Call Markup Language)

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Handwriting Recognition using Machine Learning

pcml2java-validator

PCML implementation

Point Cloud and Machine Learning

PCML project 2

:slot_machine: Mini project for pattern recognition and machine learning course

Generate node.js code from a pcml file (rpg parameters)

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Sample project to integrate with PCML/AS400 systems using WSO2 platform

Second project of PCML : implementation of a Recommander System

PCMLIA 25.3 Portfolio project on optimising a model for real-life data

Project 1 for the Pattern classification and machine learning at EPFL

Repository for the 2nd project of PCML: Recommender Systems

Assignment 17.1 for Berkeley Haas - Professional Certificate in Machine Learning and Artificial Intelligence

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Repository to keep track of machine learning projects on PCML 2014.

Extrension library for JT400 simplifying usage of ProgramCall by removing the need to use PCML or boilerplate code.

Miniproject for PCML course of Prof. Seeger at EPFL

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