A collection of data science projects which utilise machine / deep learning approaches, summarised in one place
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The full lists of all projects can be found on shtrausslearning.github.io
Project |
Description |
---|---|
Customer Transaction Predictive Analytics | Part of the Data@ANZ Internship program. The aim of the study is to analyse customer transactions & find their annual income. Based on the deduced data, we needed to create a model that will be able to predict their annual income. Two approaches were investigates, transaction based (all transactions) & customer aggregative (customer's transaction). |
Ovarian Phase Classification in Felids | In this study, we investigate feline reproductology data, conducting an exploratory data analysis of experimental measurements and attempt to find the relation between different hormone levels during different phases of pregnancy (estradiol & progesterone). We also create models that are able to predict at which stage of an estrous cycle a feline is at the time of testing for different measurement methods |
Heart Disease Classification | In this study, we explore different feature engineering approaches for classifying patients with heart disease and conduct grid searches for the two hyperparemeters in order to find the best hyperparameter configuration. We utilise an sklearn based custom Regressor model (model found here), which we turned in a classifier by simply setting the threshold to 0.5. We also utilised an ensemble of different model in order to improve the model accuracy |