Building Your First scikit-learn Solution

سرفصل های دوره

This course covers both the why and how of using scikit-learn. You'll delve into scikit-learn’s niche in the ever-growing taxonomy of machine learning libraries, and important aspects of working with scikit-learn estimators and pipelines.

1. Course Overview

1. Course Overview

2. Exploring scikit-learn for Machine Learning

01. Version Check

02. Module Overview

03. Prerequisites and Course Outline

04. Introducing Machine Learning

05. Learning from Data- Training and Prediction

06. Traditional and Representation ML Models

07. The Niche of scikit-learn in ML

08. Exploring scikit-learn Libraries

09. Supervised and Unsupervised Learning

10. Installing scikit-learn Libraries

11. Summary

3. Understanding the Machine Learning Workflow with scikit-learn

01. Module Overview

02. The Machine Learning Workflow

03. Using scikit-learn in the Machine Learning Workflow

04. Choosing the Right Estimator- Classification

05. Choosing the Right Estimator- Clustering

06. Choosing the Right Estimator- Regression and Dimensionality Reduction

07. Exploring Built-in Datasets in scikit-learn

08. Exploring the Boston Newsgroups and Digits Datasets

09. California Housing Dataset- Exploring Numeric and Categorical Features

10. California Housing Dataset- Exploring Relationships in Data

11. Summary

4. Building a Simple Machine Learning Model with scikit-learn

1. Module Overview

2. Understanding Linear Regression

3. Data Preparation for Machine Learning

4. Training and Prediction Using Linear Regression

5. Understanding Logistic Regression

6. Training and Prediction Using a Logistic Regression Classifier

7. Summary and Further Study

189,000 تومان

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خرید دانلودی فوری

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تولید کننده: PluralSight