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  1. So you're Running a Data project

    A project workflow:

    Establish the Need - what is the actual value generated by the work? This stuff only works if you have some measurable outcome for the business. This helps with the often difficult sell to upper managament!

    Produce an "ideal" solution - Dream a little - how would it work if ...

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  2. Machine Learning for the Common Man

    They say.....

    Supervised Learning

    1. Classification
    2. Regression

    You say....

    Educated Guesser given some known data

    1. Guesses words and Integer labels
    2. Guesses Real values

    They say....

    Unsupervised Learning

    1. Manifold Learning
    2. Clustering
    3. Latent Factor Analysis

    You say.....

    Explore relationships within the data

    1. Visually display relationships
    2. Group
    3. Find underlying drivers
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  3. Practical Matrix Factorization

    Introduction

    The problem in hand is to estimate unknown probabilities (missing data) in an activity matrix that indicates the interaction between small molecules and proteins. The activity matrix is initially binary, with 1 indicating positive interaction and 0 indicating an unknown interaction. The task is to replace the unknown interactions ...

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  4. Mapping and Clustering the Premiership in Python

    Introduction

    The aim of this tutorial is to gain practical experience of performing mapping and clustering, using the same premiership data-set used in the classification tutorial. This tutorial is deliberately shorter than the previous as you should be up and running with Python.

    Mapping

    Mapping is a way of letting ...

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  5. Mapping and Clustering the Premiership in R

    Introduction

    The aim of this tutorial is to gain practical experience of performing mapping and clustering, using the same premiership data-set used in the classification tutorial. This tutorial is deliberately shorter than the previous as you should be up and running with R.

    Mapping

    Mapping is a way of letting ...

    read more

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