Data Algorithms and Meaning

laptop with a coffee next to it processing some information

University of Technology Sydney subject Data, Algorithms and Meaning, focuses on developing and evaluating a variety of data science models in practical challenges and effectively communicating outcomes and value of these activities to the target audience

Assignment reports have been included as jpg images due to size and format as stop gap, this greatly reduces the accessibility of the documents despite alt-text. Once core site features are resolved and content backlog complete I will endevour to resolve this

  1. Network graph of LSA output showing 3 distinct communities connected to each other through one or two nodes, and a single unconnected node, similarity of result with clustering

    Assignment 3 Text Analysis of an Unknown Corpus

    Communicating the outcomes of analysis of an unknown corpus of documents. Developing and comparing outcomes from ‘bag of words’, TFIDF, clustering, LSA, and LDA / topic models


    Tue, Jun 16 2020

  2. Slide 8, modelling outcomes, svdf model best at 0.91 star error, recommendations, likely four of five star rating, available for 92% users, model performance comparison using RMSE

    Assignment 2 Developing a Recommender for MovieLens100K

    Communicating the business value and potential utility of data insights and a recommender model. Comparing linear regression, tree, ensemble, clustering and SVD model outputs


    Sun, May 24 2020

  3. Report Page 3, new metrics, dealer loyalty, wear, model reliability and vehicle care

    Assignment 1 Classification Modelling with Automotive Data

    Developing classification models to identify customers likely to repurchase from automotive data. Comparing GLMNET, random forest and xgboost predictions, selecting the best model and communicating outcomes to the audience


    Sun, May 3 2020

  4. Report Page 4, outcomes, deliverables, effects of variable engineering, 46% predictions less than 15% RMSE

    Assignment 1 Linear Modelling with Sales Data

    Developing linear models with R to make sales predictions and creating a report that engaged the audience while communicating outcomes


    Sun, Apr 19 2020