Linkedin Learning – Machine Learning With Scikit-Learn 2026 BOOKWARE-LERNSTUF

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                               Linkedin Learning
                       Machine Learning With Scikit-Learn
                                      2026
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 .. - -  - /- --- _- [   R E L E A S E   D E T A i L S   ]- . ./\ . - __./---' 
  Release Date : 2026-02-13
  Publisher    : Linkedin Learning
  Title        : Machine Learning With Scikit-Learn
  Year         : 2026
  Month        : January
  Category     : Artificial-Intelligence Machine-Learning
  Language     : English
  Section      : BOOKWARE
  Files        : 04 x 50 MB
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 https://www.linkedin.com/learning/machine-learning-with-scikit-learn-28473142
   The ability to apply machine learning algorithms is an important part of a
 data scientists skill set. But with so many options to choose from, it can be
 hard to know which tools you should use. scikit-learn is a popular open-source
   Python library that offers user-friendly and efficient versions of common
 machine learning algorithms. In this course, learn how to use scikit-learn for
   supervised and unsupervised machine learning. Explore the benefits of this
    powerful API and practical techniques for using it, including linear and
   logistic regression, decision trees, and random forest models, as well as
   unsupervised learning techniques such as K-means clustering and principal
   component analysis (PCA). Along the way, learn how to create scikit-learn
 pipelines to make your code cleaner and more resilient to bugs. By the end of
   this course, youll be prepared to leverage the strengths and weaknesses of
 each scikit-learn algorithm and build better, more efficient machine learning
                                    models.
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                CONTACT US ViA THE SCENE, OR EMAiL ADDRESS BELOW               
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    GREETiNGS TO ALL THE PAST AND PRESENT SCENE GROUPS AND SCENERS WHO MADE    
       STUF AVAiLABLE FOR THOSE THAT MAY NOT OTHERWISE HAD THE PRiViLEGE       
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                         lernstuf [at] proton [dot] me                         
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2.2M	001-get_started_with_machine_learning.mkv
4.2M	002-get_started_with_scikit_learn.mkv
4.6M	003-explore_machine_learning_in_the_ai_age.mkv
11M	004-discover_the_benefits_of_scikit_learn.mkv
9.9M	005-prepare_your_environment.mkv
4.8M	006-predict_values_with_supervised_learning.mkv
12M	007-format_your_data.mkv
8.9M	008-perform_a_train_test_split.mkv
11M	009-create_a_linear_regression_model.mkv
8.2M	010-leverage_logistic_regression.mkv
11M	011-evaluate_classification_models.mkv
12M	012-build_a_decision_tree.mkv
8.5M	013-rapidly_build_models_with_random_forest.mkv
9.3M	014-boost_model_performance.mkv
4.6M	015-explore_unsupervised_learning.mkv
11M	016-group_data_with_clustering_algorithms.mkv
8.6M	017-speed_up_with_dimensionality_reduction.mkv
8.2M	018-automate_preprocessing_with_pipelines.mkv
12M	019-optimize_your_hyperparameters.mkv
3.4M	020-build_models_with_scikit_learn.mkv
1.1M	Exercises
1.1M	Exercises/ex_files_ml_scikit_learn.zip
652K	LERNSTUF
648K	LERNSTUF/lernstuf_introduction_2025.rar
163M	total