Rhys Study guides, Class notes & Summaries

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WJEC applied diploma Criminology, Unit 3: AC3.2
  • WJEC applied diploma Criminology, Unit 3: AC3.2

  • Exam (elaborations) • 3 pages • 2022
  • I achieved an A* in criminology, with my Unit 3 being graded at 96%. This document includes AC3.2: Just Verdicts, Case study- Stephen Lawrence, Miscarriages of Justice, Case study- Sean Hodgson, Case Study- Stephen Downing, Safe verdicts, Just Sentencing, Case study- Ian paterson, Case Study- Rhys Hobbs and a practice link to brief.
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MNIST_Fashion_MNIST_image_data_ML_Week13_NEC MNIST_Fashion_MNIST_image_data_ML_Week13_NEC
  • MNIST_Fashion_MNIST_image_data_ML_Week13_NEC

  • Exam (elaborations) • 89 pages • 2023
  • Available in package deal
  • The main objective is to write a fully executed R-Markdown program performing clustering using DBSCAN and Mixture model on the MNIST / Fashion MNIST (apparel) images that are 28 x 28 pixels resolution. Make sure to describe the final hyperparameter settings of all algorithms that were used for comparison purposes. You are required to clearly display and explain the models that were run for this task and their effect on the reduction of the Cost Function.
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Fundamentals_of_ensemble_modeling_Week5_NEC Fundamentals_of_ensemble_modeling_Week5_NEC
  • Fundamentals_of_ensemble_modeling_Week5_NEC

  • Exam (elaborations) • 13 pages • 2023
  • Available in package deal
  • Write a fully executed R-Markdown program and submit a pdf / word or html file performing classification task using Random Forest and XGBoost algorithms on the Binary response variable from the Santander Bank Case Study. Make sure to try various hyperparameter settings of the two algorithms to find the best available models. You are required to clearly display and explain the models that were run for this task and their effect on the reduction of the Cost Function.
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Nutrition_Case_Study_ML_Week8_NEC Nutrition_Case_Study_ML_Week8_NEC
  • Nutrition_Case_Study_ML_Week8_NEC

  • Exam (elaborations) • 19 pages • 2023
  • Available in package deal
  • The main objective is to write a fully executed R-Markdown program performing regression prediction for the response variable using the best models found for LASSO, Ridge and Elastic Net techniques predicting the response variable in the Nutrition case study. Make sure to describe the final hyperparameter settings of all algorithms that were used for comparison purposes. You are required to clearly display and explain the models that were run for this task and their effect on the reduction of t...
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MNIST _Fashion_MNIST_image_data_ML_Wk12_NEC_Solved MNIST _Fashion_MNIST_image_data_ML_Wk12_NEC_Solved
  • MNIST _Fashion_MNIST_image_data_ML_Wk12_NEC_Solved

  • Exam (elaborations) • 38 pages • 2023
  • Available in package deal
  • The main objective for this week is to write a fully executed R-Markdown program performing clustering using SOM and LLE on the image data containing MNIST (digits) and Fashion MNIST (apparel) images that are 28 x 28 pixels resolution. Make sure to describe the final hyperparameter settings of all algorithms that were used for comparison purposes.
    (1)
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Fundamentals_of_general_additive_models_ML_Week7_NEC Fundamentals_of_general_additive_models_ML_Week7_NEC
  • Fundamentals_of_general_additive_models_ML_Week7_NEC

  • Exam (elaborations) • 14 pages • 2023
  • Available in package deal
  • Write a fully executed R-Markdown program and submit a pdf / word or html file performing regression task using GAM algorithms on the primary response variable in the Nutrition Case Study. Make sure to try various hyperparameter settings to find the best available models. You are required to clearly display and explain the models that were run for this task and their effect on the reduction of the Cost Function.
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Nutrition_Case_Study_ML_Week9_NEC Nutrition_Case_Study_ML_Week9_NEC
  • Nutrition_Case_Study_ML_Week9_NEC

  • Exam (elaborations) • 13 pages • 2023
  • Available in package deal
  • The main objective is to write a fully executed R-Markdown program performing regression prediction for the response variable using the best models found for kNN, Random Forest and XGBoost techniques predicting the response variable in the Nutrition case study. Make sure to describe the final hyperparameter settings of all algorithms that were used for comparison purposes. You are required to clearly display and explain the models that were run for this task and their effect on the reduction of...
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P5 Exam 1 notes - Cardiac Anatomy, Physiology and Function, Dysrhythmias
  • P5 Exam 1 notes - Cardiac Anatomy, Physiology and Function, Dysrhythmias

  • Exam (elaborations) • 36 pages • 2023
  • P5 Exam 1 notes - Cardiac Anatomy, Physiology and Function, Dysrhythmias CHAPTER 33 • Cardiovascular system o Responsible for supplying oxygen to body organs and other tissues- PERFUSION o Made up of the heart and blood vessels o Any problem with the respiratory and hematologic systems requires the CV system to work harder to meet perfusion needs • Myocardium o The heart muscle • Pericardium o Covering around the heart- PROTECTION • Right atrium receives deoxygenated blood ...
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Classification_with_Logistic_Regression_Week3_NEC Classification_with_Logistic_Regression_Week3_NEC
  • Classification_with_Logistic_Regression_Week3_NEC

  • Exam (elaborations) • 30 pages • 2023
  • Available in package deal
  • Write a fully executed R-Markdown program and submit a pdf / word or html file performing classification task on the Binary response variable from the Santander Bank Case Study. Make sure to try several permutations of the model before finding the best available model. You are required to clearly display and explain the models that were run for this task.
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Human_Activity_Recognition_Case_Analysis_ML_Week14_NEC Human_Activity_Recognition_Case_Analysis_ML_Week14_NEC
  • Human_Activity_Recognition_Case_Analysis_ML_Week14_NEC

  • Exam (elaborations) • 67 pages • 2023
  • Available in package deal
  • The main objective is to write a fully executed R-Markdown program performing EDA on the given data on the human activity recognition experiment collected through smart watches.
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