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  • U: Anonymous
  • D: 2022-03-06 16:31:03
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ReScene version pyReScene Auto 0.7 XQZT File size CRC
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37,558
Stored files
722 3CCAB61A
27,122 C67F8AAF
1,224 F092FE1F
RAR-files
linkedin.learning.machine.learning.with.logistic.regression.in.excel.r.and.power.bi-xqzt.rar 50,000,000 6FE46E33
linkedin.learning.machine.learning.with.logistic.regression.in.excel.r.and.power.bi-xqzt.r00 50,000,000 24EF326C
linkedin.learning.machine.learning.with.logistic.regression.in.excel.r.and.power.bi-xqzt.r01 50,000,000 98AD0804
linkedin.learning.machine.learning.with.logistic.regression.in.excel.r.and.power.bi-xqzt.r02 50,000,000 42DA1A46
linkedin.learning.machine.learning.with.logistic.regression.in.excel.r.and.power.bi-xqzt.r03 50,000,000 BAC854CF
linkedin.learning.machine.learning.with.logistic.regression.in.excel.r.and.power.bi-xqzt.r04 50,000,000 4CBF48AF
linkedin.learning.machine.learning.with.logistic.regression.in.excel.r.and.power.bi-xqzt.r05 50,000,000 0F707659
linkedin.learning.machine.learning.with.logistic.regression.in.excel.r.and.power.bi-xqzt.r06 50,000,000 B79E5617
linkedin.learning.machine.learning.with.logistic.regression.in.excel.r.and.power.bi-xqzt.r07 50,000,000 D36B3413
linkedin.learning.machine.learning.with.logistic.regression.in.excel.r.and.power.bi-xqzt.r08 50,000,000 70DA1F53
linkedin.learning.machine.learning.with.logistic.regression.in.excel.r.and.power.bi-xqzt.r09 50,000,000 19FB1BC2
linkedin.learning.machine.learning.with.logistic.regression.in.excel.r.and.power.bi-xqzt.r10 4,771,033 AAD2D79A

Total size: 554,771,033
Archived files
01.01-apply_logistic_regressions_to_solve_problems.mkv [bcfcf4ea6e480116] 6,396,148 898C76E6
01.02-what_you_should_know.mkv [ea6919c5f2a5ae4b] 1,289,063 9CB85C58
01.03-introduction_to_the_course_project.mkv [cbb06b6992db665b] 5,813,012 A3F5EBA9
01.04-configuring_the_excel_solver_add-in.mkv [fa9bae196e00c81d] 4,379,892 91007585
01.05-working_with_r.mkv [81435fc3258487df] 17,017,750 5A397517
01.06-configuring_r_in_power_bi.mkv [ec66149e6ce8ea32] 12,227,699 B2871A7D
02.01-introducing_ai_and_logistic_regression.mkv [184140758dff74a] 6,417,115 78EDD513
02.02-differentiating_between_odds_and_probabilities.mkv [56c3be30fb16214c] 6,146,735 5428E0D9
02.03-differentiating_between_distributions.mkv [f902f99e9da9d4ed] 4,193,394 523C5862
02.04-calculating_logs_and_exponents.mkv [ff4200d9095073af] 9,526,186 AB0D0AFD
02.05-sigmoid_curve.mkv [86a4ce772cdb5cba] 13,124,817 FE55D762
02.06-utilizing_training_and_testing_data_sets.mkv [24de124679fbe371] 7,714,591 291D07D2
03.01-calculating_linear_regression.mkv [d9190b1c2129667b] 9,100,184 F78179A3
03.02-working_with_the_logit_model.mkv [82ec679cbb08c43a] 10,709,456 24635C01
03.03-calculating_log_likelihood.mkv [4206893a8b90660e] 14,495,228 2D30A687
03.04-constructing_mle.mkv [e5d38926ce0d5b1d] 44,041,861 8BBAF291
03.05-solving_mle.mkv [9a15fd87e49eb143] 25,399,791 F14D9F4D
03.06-predicting_outcomes.mkv [be066ca768cfd6ef] 12,271,107 53C03510
03.07-visualizing_logistic_regression.mkv [a21bbe6deb18d437] 19,685,767 69CEF6D8
03.08-challenge_calculating_logistic_regression.mkv [3668532a16d2eb25] 2,213,465 601F393F
03.09-solution_calculating_logistic_regression.mkv [201d2aae18074a83] 9,949,936 3D306556
04.01-adding_more_independent_variables.mkv [8a1fa0867721c64a] 26,643,209 B7C1B2D4
04.02-transforming_variables.mkv [ac938424bc72fcca] 14,262,663 BA1C8134
04.03-calculating_correlations.mkv [1c48319df26ba636] 21,154,709 97E070C5
04.04-using_statistics.mkv [bd794cb2437e6d2b] 14,016,283 354E29EF
04.05-configuring_confusion_tables.mkv [13d1d3c124e7e6fd] 39,831,721 3448035A
04.06-challenge_fine-tuning_the_model.mkv [a7fa2a13ebcaf1bd] 2,268,395 F8D467A8
04.07-solution_fine-tuning_the_model.mkv [53ee715a145417b] 8,571,242 1005B63F
05.01-calculating_odds_for_multinomial_models.mkv [9c1b109f10c75a61] 19,150,738 EC7F9BF5
05.02-calculating_probabilities_for_multinomial_models.mkv [fcbbf855e8891c30] 9,232,409 592EA148
05.03-calculating_multinomial_log_likelihoods.mkv [ca6283b1f1f6fa06] 11,275,325 EAE2272C
05.04-running_mle.mkv [5ad7293d48593101] 18,795,245 5D7420B7
05.05-making_the_predictions.mkv [f8650be7b8d3df] 24,345,866 41C62417
06.01-running_r_scripts_in_the_power_query_editor.mkv [27a5834178523189] 24,593,459 09D1CF10
06.02-running_r_standard_visuals.mkv [801e1c4ac89b5b3d] 26,553,714 9719B40E
06.03-interacting_between_visual_components.mkv [317b17e778f393a1] 11,511,291 74F9BE75
06.04-challenge_moving_into_power_bi.mkv [fec2f6cabf78a332] 1,640,756 8C55339C
06.05-solution_moving_into_power_bi.mkv [3334c9cdadd91429] 22,342,374 D1CCC850
07.01-next_steps_with_logistic_regressions.mkv [796d65ea4ec4fd85] 2,963,379 656B09C4
Ex_Files_ML_Logistic_Regression_Excel_R_Power_BI.zip 13,500,662 F0099334

Total size: 554,766,637
Video files
Sample
linkedin.learning.machine.learning.with.logistic.regression.in.excel.r.and.power.bi-xqzt-sample.mkv 3,508,634 78976CD3
RAR Recovery
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