Implementing Machine Learning Workflow with Weka

سرفصل های دوره

In this course, you will learn how you can develop your machine learning workflow using Weka, an open-source machine learning software for data preparation, machine learning, and predictive model deployment.

1. Course Overview

1. Course Overview

02. Implementing Regression Models

01. Version Check

02. Prerequisites and Course Outline

03. Introducing Weka

04. Demo - Environment and Project Setup

05. Demo - Exploring the Weka Workbench

06. Demo - Loading and Exploring the Dataset

07. Demo - Training and Evaluating a Regression Model

08. Demo - Training and Evaluating a Multiple Regression Model

09. Demo - Feature Selection and Ranking

10. Demo - Processing and Saving Processed Data

11. Demo - Evaluating a Model Using Cross Validation

12. Demo - Regression Using Support Vector Machines and Multilayer Perceptrons

13. Demo - Serializing and Visualizing a Decision Tree Model

3. Implementing Classification Models

1. Demo - Feature Selection and Data Processing

2. Demo - Building and Evaluating a Classification Model

3. Demo - Building and Visualizing a Decision Tree Model

4. Demo - Encoding Text Data in Numeric Form

5. Demo - Performing Classification on Text Data

4. Implementing Clustering Models

1. Demo - Normalizing and Visualizing Data

2. Demo - Performing K-means Clustering

3. Demo - Visualizing Cluster Assignments

4. Demo - Exploring and Visualizing Data

5. Demo - Performing Hierarchical Clustering

6. Demo - Performing EM Clustering

7. Demo - Serializing Trained Model Parameters

8. Demo - Deploying a Model Using SpringBoot

9. Summary and Further Study

439,000 تومان

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تولید کننده: PluralSight