|
RAR-files |
| linkedin.learning.predictive.analytics.essential.training.data.mining-xqzt.rar |
50,000,000 |
B01A1357 |
| linkedin.learning.predictive.analytics.essential.training.data.mining-xqzt.r00 |
50,000,000 |
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| linkedin.learning.predictive.analytics.essential.training.data.mining-xqzt.r01 |
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| linkedin.learning.predictive.analytics.essential.training.data.mining-xqzt.r02 |
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| linkedin.learning.predictive.analytics.essential.training.data.mining-xqzt.r03 |
50,000,000 |
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| linkedin.learning.predictive.analytics.essential.training.data.mining-xqzt.r04 |
50,000,000 |
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| linkedin.learning.predictive.analytics.essential.training.data.mining-xqzt.r05 |
50,000,000 |
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| linkedin.learning.predictive.analytics.essential.training.data.mining-xqzt.r06 |
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| linkedin.learning.predictive.analytics.essential.training.data.mining-xqzt.r07 |
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| linkedin.learning.predictive.analytics.essential.training.data.mining-xqzt.r08 |
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| Total size: |
477,730,751 |
|
|
| Archived
files |
|
01.01-data_mining_and_predictive_analytics_.mkv
[efcd731b17e03b8b]
|
17,503,781 |
621E337E |
|
02.01-introducing_the_essential_elements.mkv
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|
55,377,723 |
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|
02.02-defining_data_mining.mkv
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|
13,168,094 |
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|
02.03-introducing_crisp-dm.mkv
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|
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|
03.01-beginning_with_a_solid_first_step_problem_definition.mkv
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16,399,172 |
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03.02-framing_the_problem_in_terms_of_a_micro-decision.mkv
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|
03.03-why_every_model_needs_an_effective_intervention_strategy.mkv
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|
5,834,545 |
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|
03.04-evaluate_a_projects_potential_with_business_metrics_and_roi.mkv
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|
6,130,501 |
539F0310 |
|
03.05-translating_business_problems_into_data_mining_problems.mkv
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|
8,076,870 |
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|
04.01-understanding_data_requirements.mkv
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|
23,427,269 |
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|
04.02-gathering_historical_data.mkv
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4,469,356 |
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04.03-meeting_the_flat_file_requirement.mkv
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04.04-determining_your_target_variable.mkv
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|
04.05-selecting_relevant_data.mkv
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12,701,982 |
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|
04.06-hints_on_effective_data_integration.mkv
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|
7,475,326 |
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04.07-understanding_feature_engineering.mkv
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|
7,365,027 |
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04.08-developing_your_craft.mkv
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6,146,226 |
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05.01-skill_sets_and_resources_that_youll_need.mkv
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12,122,160 |
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05.02-compare_machine_learning_and_statistics.mkv
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4,513,883 |
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05.03-assessing_team_requirements.mkv
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12,788,023 |
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05.04-budgeting_sufficient_time.mkv
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4,698,631 |
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|
05.05-working_with_subject_matter_experts.mkv
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|
7,812,199 |
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|
06.01-anticipating_project_challenges.mkv
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|
15,659,636 |
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06.02-addressing_missing_data.mkv
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|
8,489,419 |
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|
06.03-addressing_organizational_resistance.mkv
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8,843,378 |
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06.04-addressing_models_that_degrade.mkv
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|
7,362,896 |
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07.01-preparing_for_the_modeling_phase_tasks.mkv
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|
21,456,948 |
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|
07.02-searching_for_optimal_solutions.mkv
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|
14,320,472 |
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07.03-seeking_surprise_results.mkv
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|
7,752,558 |
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07.04-establishing_proof_that_the_model_works.mkv
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|
5,938,054 |
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07.05-embracing_a_trial_and_error_approach.mkv
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|
4,298,237 |
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08.01-preparing_for_the_deployment_phase.mkv
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|
16,015,048 |
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|
08.02-using_probabilities_and_propensities.mkv
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|
7,884,254 |
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08.03-understanding_meta_modeling.mkv
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|
11,481,692 |
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08.04-understanding_reproducibility.mkv
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|
7,082,321 |
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08.05-preparing_for_model_deployment.mkv
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3,517,716 |
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08.06-how_to_approach_project_documentation.mkv
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|
8,351,870 |
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09.01-crisp-dm_and_the_laws_of_data_mining.mkv
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|
16,381,957 |
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09.02-understanding_crisp-dm.mkv
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5,561,287 |
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09.03-advice_for_using_crisp-dm.mkv
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|
9,398,459 |
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09.04-understanding_the_nine_laws_of_data_mining.mkv
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4,698,327 |
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09.05-understanding_the_first_and_second_laws.mkv
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|
3,864,394 |
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09.06-understanding_the_data_preparation_law.mkv
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12,787,342 |
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09.07-understanding_the_laws_about_patterns.mkv
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|
12,591,292 |
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09.08-understanding_the_insight_and_prediction_laws.mkv
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6,891,713 |
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09.09-understanding_the_value_law.mkv
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|
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09.10-understanding_why_models_change.mkv
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10.01-next_steps.mkv
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4,163,506 |
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| Total size: |
477,725,726 |
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|
