Module: Machine Learning

Eportfolio of work done on my Machine Learning module at the University of Essex

Units

A breakdown of each unit including the e-Portfolio and formative activities.

• Units 1- 3

  • Collaborative Discussion 1: The 4th Industrial Revolution
    • Initial Post
    • Peer Response to Marwa Alkuwari
    • Peer Response to Noora Alboinin
    • Summary Post

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• Unit 2

  • Artefact:
    • Exploratory Data Analysis: A tutorial on conducting exploratory data analysis as part of the machine learning process.

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• Unit 3

  • Artefacts:
    • Covariance Pearson Correlation
    • Linear Regression
    • Multiple Linear Regression
    • Polynomial Regression

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• Unit 4

  • Unit 4 Seminar Preparation:
    • Task A & Task B: Correlation & Regression

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• Unit 5

  • Wiki Activity
  • Artefact:
    • Jaccard Coefficient Calculations

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• Unit 6

  • Artefacts:
    • Task A: K-Means Clustering on Iris Dataset
    • Task B: K-Means Clustering on Wine Dataset
    • Task C: K-Means Clustering on WeatherAUS Dataset
  • Development Team Project: Airbnb business analysis using data science approach

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• Unit 7

  • Perceptron Activities: Involved running the given notebooks showing simple perceptron, and multi-layer perceptrons.

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• Unit 8

  • Gradient Cost Function: Involved running the given notebook, experimenting with gradient cost function.

• Unit 8 - 10

  • Collaborative Discussion 2: Legal and Ethical views on ANN applications
    • Initial Post
    • Peer Response to Md Aminur Rahman
    • Peer Response to Noora Alboinin
    • Summary Post

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• Unit 9

  • Artefacts:
    • CNN Model Activity

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• Unit 11

  • e-Portfolio Activity: Model Performance Measurement: Involved running the given notebook, experimenting model performance measurement
  • Development Individual Project: Presentation:
    • Slides
    • Oral Transcript
    • Video

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• Unit 12

  • Artefacts:
    • Descriptive/predictive/prescriptive) prognostic machine learning model used in industry 4.0.
    • Reflective Essay

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