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IBM Introduction to Machine Learning Specialization 2024

IBM Introduction to Machine Learning Specialization 2024

Coursera - IBM Introduction to Machine Learning Specialization 2024-2

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Responsible Narodom.guy
Last Update 04/07/2024
Completion Time 19 minutes
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  • 1Lessons ·
    • 01_course-introduction.mp4
  • 6Lessons · 10 min
    • 01_introduction-to-artificial-intelligence-and-machine-learning.mp4
    • 02_machine-learning-and-deep-learning.mp4
    • 03_machine-learning-and-deep-learning-part-1.mp4
    • 04_machine-learning-and-deep-learning-part-2.mp4
    • 05_history-of-ai.mp4
    • 06_history-of-machine-learning-and-deep-learning.mp4
  • 3Lessons ·
    • 01_modern-ai.mp4
    • 02_applications.mp4
    • 03_machine-learning-workflow.mp4
  • 4Lessons ·
    • 01_retrieving-data-from-csv-and-json-files.mp4
    • 02_retrieving-data-from-databases-apis-and-the-cloud.mp4
    • 04_optional-lab-solution-reading-data-jupyter-notebook-part-a.mp4
    • 06_optional-lab-solution-reading-in-database-files-part-b.mp4
  • 3Lessons ·
    • 01_data-cleaning.mp4
    • 02_handling-missing-values-and-outliers.mp4
    • 03_handling-missing-values-and-outliers-using-residuals.mp4
  • 7Lessons ·
    • 01_introduction-to-exploratory-data-analysis-eda.mp4
    • 02_eda-with-visualization.mp4
    • 03_grouping-data-for-eda.mp4
    • 05_optional-solution-eda-notebook-part-1.mp4
    • 06_optional-solution-eda-notebook-part-2.mp4
    • 07_optional-solution-eda-notebook-part-3.mp4
    • 08_optional-solution-eda-notebook-part-4.mp4
  • 8Lessons ·
    • 01_feature-engineering-and-variable-transformation-background.mp4
    • 02_variable-transformation.mp4
    • 03_feature-encoding.mp4
    • 04_feature-scaling.mp4
    • 05_common-variable-transformations-in-python.mp4
    • 07_optional-solution-feature-engineering-lab-part-1.mp4
    • 08_optional-solution-feature-engineering-lab-part-2.mp4
    • 09_optional-solution-feature-engineering-lab-part-3.mp4
  • 6Lessons ·
    • 01_estimation-and-inference-introduction.mp4
    • 02_estimation-and-inference-example.mp4
    • 03_estimation-and-inference-parametric-vs-non-parametric.mp4
    • 04_estimation-and-inference-commonly-used-distributions.mp4
    • 05_curse-of-dimensionality-notebook-part-3.mp4
    • 06_mean-shift.mp4
  • 4Lessons ·
    • 01_course-introduction.mp4
    • 02_introduction-to-unsupervised-learning-overview.mp4
    • 03_introduction-to-unsupervised-learning-use-cases-of-clustering.mp4
    • 04_introduction-to-clustering.mp4
  • 7Lessons · 4 min
    • 01_k-means.mp4
    • 02_k-means-initialization.mp4
    • 03_selecting-the-right-number-of-clusters-in-k-means.mp4
    • 04_elbow-method-and-applying-k-means.mp4
    • 05_optional-k-means-notebook-part-1.mp4
    • 06_k-means-notebook-part-2.mp4
    • 07_optional-k-means-notebook-part-3.mp4
  • 6Lessons ·
    • 01_distance-metrics-euclidean-and-manhattan-distance.mp4
    • 02_distance-metrics-cosine-and-jaccard-distance.mp4
    • 03_curse-of-dimensionality-notebook-part-1.mp4
    • 04_curse-of-dimensionality-notebook-part-2.mp4
    • 05_curse-of-dimensionality-notebook-part-3.mp4
    • 06_curse-of-dimensionality-notebook-part-4.mp4
  • 6Lessons · 5 min
    • 01_hierarchical-agglomerative-clustering.mp4
    • 02_hierarchical-agglomerative-clustering-hierarchical-linkage-types.mp4
    • 03_applying-hierarchical-agglomerative-clustering.mp4
    • 04_dbscan.mp4
    • 05_visualizing-dbscan.mp4
    • 06_mean-shift.mp4
  • 5Lessons ·
    • 01_comparing-algorithms.mp4
    • 02_clustering-notebook-part-1.mp4
    • 03_clustering-notebook-part-2.mp4
    • 04_optional-clustering-notebook-part-3.mp4
    • 05_clustering-notebook-part-4.mp4
  • 2Lessons ·
    • 01_kernel-principal-component-analysis-and-multidimensional-scaling.mp4
    • 02_dimensionality-reduction-notebook-part-3.mp4
  • 3Lessons ·
    • 01_non-negative-matrix-factorization.mp4
    • 02_non-negative-matrix-factorization-notebook-part-1.mp4
    • 03_non-negative-matrix-factorization-notebook-part-2.mp4