Building Machine Learning Solutions with scikit-learn (Path)

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This skill teaches learners how to build machine learning solutions using Python and the pervasive scikit-learn package, including application of classifcation, regression, and clustering.

Experience the machine learning workflow as implemented in scikit-learn, and use that workflow to build simple classification, regression, and clustering models.
Build sophisticated neural network models, apply dimension reduction techniques, and combine model approaches.
Select the appropriate model for your business problem and data, and evaluate the effectiveness of that model.

Courses in this path

A1. Building Your First scikit-learn Solution (Janani Ravi, 2019)
A2. Building Classification Models with scikit-learn (Janani Ravi, 2019)
A3. Building Regression Models with scikit-learn (Janani Ravi, 2019)
A4. Building Clustering Models with scikit-learn (Janani Ravi, 2019)
B1. Building Neural Networks with scikit-learn (Janani Ravi, 2019)
B2. Reducing Dimensions in Data with scikit-learn (Janani Ravi, 2019)
B3. Employing Ensemble Methods with scikit-learn (Janani Ravi, 2019)
C1. Preparing Data for Modeling with scikit-learn (Janani Ravi, 2019)
C2. Scaling scikit-learn Solutions (Janani Ravi, 2019)
C3. Model Evaluation and Selection Using scikit-learn (Chetan Prabhu, 2019)

HomePage:

https://anonymz.com/https://www.pluralsight.com/paths/building-machine-learning-solutions-with-scikit-learn

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