IBM Introduction to Machine Learning Specialization 2024
Coursera - IBM Introduction to Machine Learning Specialization 2024-2
Responsible | Narodom Narodom.guy |
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Last Update | 04/07/2024 |
Completion Time | 19 minutes |
Members | 1 |
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01.1_course-introduction1Lessons ·
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01_course-introduction.mp4
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01.2_introduction-to-artificial-intelligence-and-machine-learning6Lessons · 10 min
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01_introduction-to-artificial-intelligence-and-machine-learning.mp4
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02_machine-learning-and-deep-learning.mp4
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03_machine-learning-and-deep-learning-part-1.mp4
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04_machine-learning-and-deep-learning-part-2.mp4
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05_history-of-ai.mp4
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06_history-of-machine-learning-and-deep-learning.mp4
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01.3_modern-ai-applications-and-the-machine-learning-workflow3Lessons ·
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01_modern-ai.mp4
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02_applications.mp4
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03_machine-learning-workflow.mp4
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02.1_retrieving-data4Lessons ·
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01_retrieving-data-from-csv-and-json-files.mp4
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02_retrieving-data-from-databases-apis-and-the-cloud.mp4
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04_optional-lab-solution-reading-data-jupyter-notebook-part-a.mp4
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06_optional-lab-solution-reading-in-database-files-part-b.mp4
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02.2_data-cleaning3Lessons ·
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01_data-cleaning.mp4
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02_handling-missing-values-and-outliers.mp4
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03_handling-missing-values-and-outliers-using-residuals.mp4
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03.1_exploratory-data-analysis7Lessons ·
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01_introduction-to-exploratory-data-analysis-eda.mp4
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02_eda-with-visualization.mp4
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03_grouping-data-for-eda.mp4
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05_optional-solution-eda-notebook-part-1.mp4
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06_optional-solution-eda-notebook-part-2.mp4
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07_optional-solution-eda-notebook-part-3.mp4
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08_optional-solution-eda-notebook-part-4.mp4
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03.2_feature-engineering-and-variable-transformation8Lessons ·
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01_feature-engineering-and-variable-transformation-background.mp4
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02_variable-transformation.mp4
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03_feature-encoding.mp4
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04_feature-scaling.mp4
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05_common-variable-transformations-in-python.mp4
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07_optional-solution-feature-engineering-lab-part-1.mp4
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08_optional-solution-feature-engineering-lab-part-2.mp4
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09_optional-solution-feature-engineering-lab-part-3.mp4
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04.1_estimation-and-inference-and-hypothesis-testing6Lessons ·
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01_estimation-and-inference-introduction.mp4
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02_estimation-and-inference-example.mp4
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03_estimation-and-inference-parametric-vs-non-parametric.mp4
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04_estimation-and-inference-commonly-used-distributions.mp4
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05_curse-of-dimensionality-notebook-part-3.mp4
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06_mean-shift.mp4
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01.1_introduction-to-unsupervised-learning4Lessons ·
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01_course-introduction.mp4
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02_introduction-to-unsupervised-learning-overview.mp4
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03_introduction-to-unsupervised-learning-use-cases-of-clustering.mp4
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04_introduction-to-clustering.mp4
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01.2_k-means-clustering7Lessons · 4 min
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01_k-means.mp4
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02_k-means-initialization.mp4
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03_selecting-the-right-number-of-clusters-in-k-means.mp4
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04_elbow-method-and-applying-k-means.mp4
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05_optional-k-means-notebook-part-1.mp4
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06_k-means-notebook-part-2.mp4
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07_optional-k-means-notebook-part-3.mp4
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02.1_computational-hurdles-of-clustering-algorithms6Lessons ·
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01_distance-metrics-euclidean-and-manhattan-distance.mp4
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02_distance-metrics-cosine-and-jaccard-distance.mp4
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03_curse-of-dimensionality-notebook-part-1.mp4
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04_curse-of-dimensionality-notebook-part-2.mp4
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05_curse-of-dimensionality-notebook-part-3.mp4
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06_curse-of-dimensionality-notebook-part-4.mp4
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03.1_common-clustering-algorithms6Lessons · 5 min
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01_hierarchical-agglomerative-clustering.mp4
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02_hierarchical-agglomerative-clustering-hierarchical-linkage-types.mp4
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03_applying-hierarchical-agglomerative-clustering.mp4
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04_dbscan.mp4
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05_visualizing-dbscan.mp4
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06_mean-shift.mp4
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03.2_comparing-clustering-algorithms5Lessons ·
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01_comparing-algorithms.mp4
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02_clustering-notebook-part-1.mp4
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03_clustering-notebook-part-2.mp4
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04_optional-clustering-notebook-part-3.mp4
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05_clustering-notebook-part-4.mp4
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05.1_kernel-principal-component-analysis-and-multidimensional-scaling2Lessons ·
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01_kernel-principal-component-analysis-and-multidimensional-scaling.mp4
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02_dimensionality-reduction-notebook-part-3.mp4
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06.1_matrix-factorization3Lessons ·
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01_non-negative-matrix-factorization.mp4
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02_non-negative-matrix-factorization-notebook-part-1.mp4
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03_non-negative-matrix-factorization-notebook-part-2.mp4
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