K1 Study guides, Class notes & Summaries

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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
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  • 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.
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AFK1506 ASSIGNMENT 3 2022
  • AFK1506 ASSIGNMENT 3 2022

  • Other • 8 pages • 2022
  • Answers available for AFK1506 ASSIGNMENT 3. THIS IS A GREAT GUIDE.
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AFK1503 ASSESSMENT 1 2024 (ANSWERS)
  • AFK1503 ASSESSMENT 1 2024 (ANSWERS)

  • Exam (elaborations) • 7 pages • 2024
  • AFK1503 WERKOPDRAG 1 ASSESSMENT 1 2024 (338539) - DUE 9 April 2024 [2200 SAST .... 100% TRUSTED workings with detailed answers.
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 LSK152 Legal Skills Assignment Solutions 2023 01  LSK152 Legal Skills Assignment Solutions 2023 01
  • LSK152 Legal Skills Assignment Solutions 2023 01

  • Other • 17 pages • 2023
  • LSK152 Legal Skills Assignment Solutions 2023 01
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Text_Analytics_Week13_NEC_Solved Text_Analytics_Week13_NEC_Solved
  • Text_Analytics_Week13_NEC_Solved

  • Exam (elaborations) • 19 pages • 2023
  • Available in package deal
  • Create time series charts for each tweeter showing how word usage has changed over time. Show for three words. You may have to manipulate a parameter to show Comment your code, line by line. Show a graph for each tweeter revealing the ten words with the highest number of retweets. Comment your code, line by line.
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Text_Analytics_Week12_NEC_Solved Text_Analytics_Week12_NEC_Solved
  • Text_Analytics_Week12_NEC_Solved

  • Exam (elaborations) • 13 pages • 2023
  • Available in package deal
  • Using the attached files of around 3200 tweets per person, show a histogram (frequency distribution) of the tweets of both Dave and Julia. Use `UTC` to create the time stamp. Remember that the case of column headers matters. Make a dataframe of word frequency for each of Dave and Julia. Plot the frequencies against each other. Include a dividing line in red showing words nearby that are similar in frequency and words more distant which are shared less frequently. Create a stacked chart compa...
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Drawing_Maps_VisualAnalytics_Week14_NEC_Solved Drawing_Maps_VisualAnalytics_Week14_NEC_Solved
  • Drawing_Maps_VisualAnalytics_Week14_NEC_Solved

  • Exam (elaborations) • 11 pages • 2023
  • 1. pipe the election data through the select() function to pick out the following columns - state, total_vote, r_points, pct_trump, party, census. Pipe that through sample() to see the first five rows. 2. Create a state level dotplot of election data except the District of Columbia faceted by region. Colorize the dots by party and insert a vertical line dividing the parties, scale the x axis from -30 to +40, put the states on the y axis and label each facet by region and the entire set by "Po...
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NRS 493 Week1-ISP.
  • NRS 493 Week1-ISP.

  • Exam (elaborations) • 10 pages • 2023
  • NRS 493 Week1-ISP.100% TRUSTED Answers, guidelines, workings and references.
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FRK121 notes
  • FRK121 notes

  • Summary • 48 pages • 2023
  • Notes for chapters 1-4 and 6-10 1. Non current assets 2. Inventory 3. Liabilities 4. Salaries 6. Analysis and interpretation 7. Partnerships 8. Companies 9. Non-profit entities 10. Statement of cash flows
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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
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  • 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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