[CourseClub.Me] Pluralsight - Building Machine Learning Solutions With Java - Learning Paths

Creation Time	May 1, 2024, 5:02 a.m.
Last Access Time	Jan. 2, 2026, 6:44 p.m.
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Keywords	Me Building Pluralsight Java CourseClub Paths - Machine Solutions Learning With
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Total Files	268
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2. Exploring Java Machine Learning Environments/exercise.zip 82.3 MB
1. Preparing Data for Machine Learning with Java/5. Data Transformation/4. Demo - Data Transformation Pipeline.mp4 34.4 MB
1. Preparing Data for Machine Learning with Java/6. Data Preparation at Scale/5. Demo - Developing Beam SDK Pipelines.mp4 34.2 MB
2. Exploring Java Machine Learning Environments/4. Implementing a Machine Learning Workflow with DL4J/4. Demo - Data Preprocessing with DL4J.mp4 32.0 MB
1. Preparing Data for Machine Learning with Java/2. Ingesting Data from Files in Various Formats/5. Demo - Ingestion.mp4 28.7 MB
2. Exploring Java Machine Learning Environments/4. Implementing a Machine Learning Workflow with DL4J/3. Demo - Data Preparation and Loading with DL4J (Part 2 - DL4J DataSetIt.mp4 28.1 MB
1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/8. Demo - Coding for Selenium.mp4 27.0 MB
1. Preparing Data for Machine Learning with Java/exercise.zip 26.0 MB
1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/4. Demo - Using the File Watcher API.mp4 26.0 MB
3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/3. Demo - Visualizing Cluster Assignments.mp4 24.8 MB
3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/08. Demo - Training and Evaluating a Multiple Regression Model.mp4 24.8 MB
1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/5. Demo - Using the Quartz Scheduler Library.mp4 24.7 MB
3. Implementing Machine Learning Workflow with Weka/3. Implementing Classification Models/5. Demo - Performing Classification on Text Data.mp4 23.7 MB
3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/09. Demo - Feature Selection and Ranking.mp4 23.1 MB
3. Implementing Machine Learning Workflow with Weka/3. Implementing Classification Models/4. Demo - Encoding Text Data in Numeric Form.mp4 22.9 MB
3. Implementing Machine Learning Workflow with Weka/3. Implementing Classification Models/2. Demo - Building and Evaluating a Classification Model.mp4 22.4 MB
3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/8. Demo - Deploying a Model Using SpringBoot.mp4 21.8 MB
4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/07. Demo - Building and Evaluating a Logistic Regression Classification .mp4 21.7 MB
3. Implementing Machine Learning Workflow with Weka/3. Implementing Classification Models/1. Demo - Feature Selection and Data Processing.mp4 21.2 MB
4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/03. Demo - Loading and Exploring Data.mp4 21.1 MB
4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/09. Demo - Performing Clustering and Evaluating Clustering Models.mp4 21.1 MB
3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/13. Demo - Serializing and Visualizing a Decision Tree Model.mp4 20.9 MB
2. Exploring Java Machine Learning Environments/4. Implementing a Machine Learning Workflow with DL4J/5. Demo - Implementing a Twitter Sentiment Classifier with DL4J.mp4 20.4 MB
3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/10. Demo - Processing and Saving Processed Data.mp4 20.3 MB
3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/1. Demo - Normalizing and Visualizing Data.mp4 20.1 MB
1. Preparing Data for Machine Learning with Java/4. Data Cleaning Using Regex and Formatter/5. Demo - Data Cleaning Pipeline.mp4 19.6 MB
4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/06. Demo - Exploring the Dataset.mp4 19.1 MB
4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/12. Demo - Train a Model with Normalized Data.mp4 18.6 MB
2. Exploring Java Machine Learning Environments/5. Implementing a Machine Learning Workflow with Spark MLlib/3. Demo - Data Preprocessing with Spark MLlib.mp4 18.4 MB
3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/07. Demo - Training and Evaluating a Regression Model.mp4 18.1 MB
4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/06. Demo - Performing Predictions Using the Classification Model.mp4 17.4 MB
4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/11. Demo - Assign Roles and Perform Attribute Selection.mp4 16.5 MB
4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/04. Demo - Building and Training a Regression Model.mp4 16.3 MB
4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/09. Demo - Using a Pretrained Model for Image Segmentation.mp4 16.1 MB
4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/02. Demo - Getting Set up with a Maven Project.mp4 16.1 MB
2. Exploring Java Machine Learning Environments/2. Understanding the Java Machine Learning Ecosystem/5. Demo - Spark MLlib Showcase.mp4 16.0 MB
4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/07. Demo - Build and Evaluate a Linear Regression Model.mp4 15.7 MB
2. Exploring Java Machine Learning Environments/3. Implementing a Machine Learning Workflow with Weka/5. Demo - Evaluation and Visualization with Programmatic Weka.mp4 15.5 MB
4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/11. Demo - Making Predictions Using a Deployed Model.mp4 15.3 MB
3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/05. Demo - Exploring the Weka Workbench.mp4 15.0 MB
4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/10. Demo - Evaluate a Model Using Cross-validation.mp4 15.0 MB
3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/5. Demo - Performing Hierarchical Clustering.mp4 14.9 MB
1. Preparing Data for Machine Learning with Java/2. Ingesting Data from Files in Various Formats/1. Introduction.mp4 14.9 MB
2. Exploring Java Machine Learning Environments/2. Understanding the Java Machine Learning Ecosystem/4. Demo - Deeplearning4j (DL4J) Showcase.mp4 14.8 MB
3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/06. Demo - Loading and Exploring the Dataset.mp4 14.7 MB
3. Implementing Machine Learning Workflow with Weka/3. Implementing Classification Models/3. Demo - Building and Visualizing a Decision Tree Model.mp4 14.7 MB
4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/10. Demo - Serializing and Deserializing Trained Models.mp4 14.3 MB
1. Preparing Data for Machine Learning with Java/6. Data Preparation at Scale/1. Introduction.mp4 13.9 MB
4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/04. Demo - Building a Fully Connected Neural Network for Image Classifica.mp4 13.6 MB
1. Preparing Data for Machine Learning with Java/6. Data Preparation at Scale/6. Demo - Deploying Beam SDK Pipelines to GCP Dataflow.mp4 13.5 MB
4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/08. Demo - Using a Pretrained Model for Image Classification.mp4 13.1 MB
4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/05. Demo - Setting up a Repository and Importing Data.mp4 12.7 MB
3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/7. Demo - Serializing Trained Model Parameters.mp4 12.6 MB
3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/2. Demo - Performing K-means Clustering.mp4 12.4 MB
2. Exploring Java Machine Learning Environments/4. Implementing a Machine Learning Workflow with DL4J/2. Demo - Data Preparation and Loading with DL4J (Part 1 - Setup).mp4 12.2 MB
4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/06. Demo - Training and Evaluating a Ridge Regression Model.mp4 12.1 MB
2. Exploring Java Machine Learning Environments/5. Implementing a Machine Learning Workflow with Spark MLlib/2. Demo - Data Preparation and Loading with Spark MLlib.mp4 12.1 MB
4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/05. Demo - Evaluating a Regression Model.mp4 12.1 MB
1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/1. Introduction.mp4 12.1 MB
3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/12. Demo - Regression Using Support Vector Machines and Multilayer Perceptrons.mp4 11.9 MB
4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/11. Demo - Answering Questions with Google BERT.mp4 11.7 MB
1. Preparing Data for Machine Learning with Java/4. Data Cleaning Using Regex and Formatter/1. Introduction.mp4 11.7 MB
4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/09. Demo - Perform Attribute Selection.mp4 11.3 MB
3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/04. Demo - Environment and Project Setup.mp4 11.2 MB
1. Preparing Data for Machine Learning with Java/2. Ingesting Data from Files in Various Formats/3. Ingesting CSV and Excel Files.mp4 11.0 MB
2. Exploring Java Machine Learning Environments/3. Implementing a Machine Learning Workflow with Weka/6. Demo - The Full Workflow in One Go with Weka GUI.mp4 10.9 MB
2. Exploring Java Machine Learning Environments/2. Understanding the Java Machine Learning Ecosystem/3. Demo - Weka Showcase.mp4 10.4 MB
2. Exploring Java Machine Learning Environments/3. Implementing a Machine Learning Workflow with Weka/2. Demo - Data Preparation and Loading with Programmatic Weka.mp4 10.4 MB
4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/04. Demo - Download and Setup RapidMiner.mp4 10.4 MB
4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/08. Demo - Train Model on Training Data and Evaluate Using T.mp4 10.3 MB
3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/6. Demo - Performing EM Clustering.mp4 10.3 MB
3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/4. Demo - Exploring and Visualizing Data.mp4 10.0 MB
1. Preparing Data for Machine Learning with Java/5. Data Transformation/3. Scaling, Data Skew, and Data Bias.mp4 9.8 MB
1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/2. Folder Monitoring.mp4 9.6 MB
1. Preparing Data for Machine Learning with Java/6. Data Preparation at Scale/4. Beam SDK Engines and GCP Dataflow.mp4 9.5 MB
4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/05. Demo - Training the Image Classification Model.mp4 9.0 MB
1. Preparing Data for Machine Learning with Java/4. Data Cleaning Using Regex and Formatter/2. Lambdas and Streams.mp4 8.8 MB
1. Preparing Data for Machine Learning with Java/4. Data Cleaning Using Regex and Formatter/4. Using Regular Expressions in Java.mp4 8.5 MB
2. Exploring Java Machine Learning Environments/5. Implementing a Machine Learning Workflow with Spark MLlib/1. Introduction.mp4 8.4 MB
3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/11. Demo - Evaluating a Model Using Cross Validation.mp4 7.8 MB
1. Preparing Data for Machine Learning with Java/5. Data Transformation/1. Introduction.mp4 7.6 MB
1. Preparing Data for Machine Learning with Java/2. Ingesting Data from Files in Various Formats/4. Ingesting JSON and XML Files.mp4 7.5 MB
2. Exploring Java Machine Learning Environments/3. Implementing a Machine Learning Workflow with Weka/1. Introduction.mp4 7.5 MB
2. Exploring Java Machine Learning Environments/5. Implementing a Machine Learning Workflow with Spark MLlib/5. Demo - Performance and Evaluation and Visualization with Spark .mp4 7.5 MB
1. Preparing Data for Machine Learning with Java/4. Data Cleaning Using Regex and Formatter/3. Regular Expressions Overview.mp4 7.5 MB
1. Preparing Data for Machine Learning with Java/5. Data Transformation/2. Data Transformation Basics.mp4 7.4 MB
2. Exploring Java Machine Learning Environments/4. Implementing a Machine Learning Workflow with DL4J/1. Introduction.mp4 7.3 MB
1. Preparing Data for Machine Learning with Java/6. Data Preparation at Scale/3. Beam SDK Concepts.mp4 6.9 MB
2. Exploring Java Machine Learning Environments/4. Implementing a Machine Learning Workflow with DL4J/6. Demo - Performance and Evaluation and Visualization with DL4J.mp4 6.6 MB
1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/7. Demo - Using the Selenium IDE.mp4 6.6 MB
2. Exploring Java Machine Learning Environments/2. Understanding the Java Machine Learning Ecosystem/2. Introduction.mp4 6.4 MB
4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/08. Demo - Building and Evaluating a Decision Tree Classification Model.mp4 6.4 MB
4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/07. Brief Overview of Transfer Learning.mp4 6.2 MB
1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/3. Task Scheduling.mp4 6.1 MB
2. Exploring Java Machine Learning Environments/5. Implementing a Machine Learning Workflow with Spark MLlib/4. Demo - Implementing an Image Classifier with Spark MLlib.mp4 5.7 MB
1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/6. Selenium.mp4 5.7 MB
1. Preparing Data for Machine Learning with Java/6. Data Preparation at Scale/2. Distributed Data Pipelines.mp4 5.6 MB
4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/01. Introducing DJL.mp4 5.5 MB
4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/01. Introducing JSAT.mp4 5.3 MB
4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/03. Demo - Setting up the Maven Project and Dependencies.mp4 5.3 MB
4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/02. Brief Overview of Neural Networks.mp4 5.1 MB
1. Preparing Data for Machine Learning with Java/1. Course Overview/1. Course Overview.mp4 4.7 MB
4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/03. Introducing RapidMiner.mp4 4.4 MB
4. Implementing Machine Learning Workflow with RapidMiner/exercise.zip 4.4 MB
2. Exploring Java Machine Learning Environments/3. Implementing a Machine Learning Workflow with Weka/3. Demo - Data Preprocessing with Programmatic Weka.mp4 4.1 MB
4. Implementing Machine Learning Workflow with RapidMiner/1. Course Overview/1. Course Overview.mp4 4.0 MB
3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/03. Introducing Weka.mp4 4.0 MB
3. Implementing Machine Learning Workflow with Weka/1. Course Overview/1. Course Overview.mp4 4.0 MB
2. Exploring Java Machine Learning Environments/1. Course Overview/1. Course Overview.mp4 3.9 MB
4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/02. Prerequisites and Course Outline.mp4 3.8 MB
3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/02. Prerequisites and Course Outline.mp4 3.6 MB
2. Exploring Java Machine Learning Environments/3. Implementing a Machine Learning Workflow with Weka/4. Demo - Implementing K-means with Programmatic Weka.mp4 3.6 MB
1. Preparing Data for Machine Learning with Java/6. Data Preparation at Scale/8. Wrap Up.mp4 2.8 MB
2. Exploring Java Machine Learning Environments/2. Understanding the Java Machine Learning Ecosystem/6. Summary.mp4 2.6 MB
3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/9. Summary and Further Study.mp4 2.6 MB
4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/12. Summary and Further Study.mp4 2.5 MB
4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/10. Introducing Google BERT.mp4 2.3 MB
3. Implementing Machine Learning Workflow with Weka/exercise.zip 2.2 MB
1. Preparing Data for Machine Learning with Java/2. Ingesting Data from Files in Various Formats/2. What Is Data Preparation.mp4 1.9 MB
2. Exploring Java Machine Learning Environments/4. Implementing a Machine Learning Workflow with DL4J/7. Summary.mp4 1.1 MB
1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/9. Summary.mp4 1.1 MB
1. Preparing Data for Machine Learning with Java/2. Ingesting Data from Files in Various Formats/6. Summary.mp4 1.0 MB
2. Exploring Java Machine Learning Environments/3. Implementing a Machine Learning Workflow with Weka/7. Summary.mp4 1006.7 KB
1. Preparing Data for Machine Learning with Java/6. Data Preparation at Scale/7. Summary.mp4 954.9 KB
2. Exploring Java Machine Learning Environments/5. Implementing a Machine Learning Workflow with Spark MLlib/6. Summary.mp4 943.4 KB
1. Preparing Data for Machine Learning with Java/5. Data Transformation/5. Summary.mp4 818.2 KB
1. Preparing Data for Machine Learning with Java/4. Data Cleaning Using Regex and Formatter/6. Summary.mp4 640.1 KB
4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/01. Version Check.mp4 546.5 KB
3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/01. Version Check.mp4 516.2 KB
2. Exploring Java Machine Learning Environments/2. Understanding the Java Machine Learning Ecosystem/1. Version Check.mp4 375.8 KB
2. Exploring Java Machine Learning Environments/4. Implementing a Machine Learning Workflow with DL4J/4. Demo - Data Preprocessing with DL4J.vtt 9.9 KB
4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/06. Demo - Exploring the Dataset.vtt 9.9 KB
3. Implementing Machine Learning Workflow with Weka/3. Implementing Classification Models/5. Demo - Performing Classification on Text Data.vtt 9.8 KB
1. Preparing Data for Machine Learning with Java/5. Data Transformation/4. Demo - Data Transformation Pipeline.vtt 9.7 KB
1. Preparing Data for Machine Learning with Java/5. Data Transformation/3. Scaling, Data Skew, and Data Bias.vtt 9.4 KB
3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/8. Demo - Deploying a Model Using SpringBoot.vtt 9.3 KB
3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/09. Demo - Feature Selection and Ranking.vtt 9.2 KB
1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/2. Folder Monitoring.vtt 9.0 KB
1. Preparing Data for Machine Learning with Java/6. Data Preparation at Scale/4. Beam SDK Engines and GCP Dataflow.vtt 9.0 KB
3. Implementing Machine Learning Workflow with Weka/3. Implementing Classification Models/1. Demo - Feature Selection and Data Processing.vtt 8.9 KB
4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/12. Demo - Train a Model with Normalized Data.vtt 8.9 KB
4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/06. Demo - Performing Predictions Using the Classification Model.vtt 8.8 KB
1. Preparing Data for Machine Learning with Java/4. Data Cleaning Using Regex and Formatter/2. Lambdas and Streams.vtt 8.7 KB
3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/13. Demo - Serializing and Visualizing a Decision Tree Model.vtt 8.7 KB
3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/1. Demo - Normalizing and Visualizing Data.vtt 8.5 KB
1. Preparing Data for Machine Learning with Java/2. Ingesting Data from Files in Various Formats/3. Ingesting CSV and Excel Files.vtt 8.5 KB
4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/04. Demo - Building a Fully Connected Neural Network for Image Classifica.vtt 8.5 KB
1. Preparing Data for Machine Learning with Java/6. Data Preparation at Scale/5. Demo - Developing Beam SDK Pipelines.vtt 8.4 KB
4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/09. Demo - Performing Clustering and Evaluating Clustering Models.vtt 8.4 KB
4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/11. Demo - Making Predictions Using a Deployed Model.vtt 8.3 KB
3. Implementing Machine Learning Workflow with Weka/3. Implementing Classification Models/2. Demo - Building and Evaluating a Classification Model.vtt 8.2 KB
1. Preparing Data for Machine Learning with Java/2. Ingesting Data from Files in Various Formats/5. Demo - Ingestion.vtt 8.2 KB
4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/07. Demo - Building and Evaluating a Logistic Regression Classification .vtt 8.1 KB
2. Exploring Java Machine Learning Environments/4. Implementing a Machine Learning Workflow with DL4J/3. Demo - Data Preparation and Loading with DL4J (Part 2 - DL4J DataSetIt.vtt 8.1 KB
1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/4. Demo - Using the File Watcher API.vtt 8.0 KB
3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/3. Demo - Visualizing Cluster Assignments.vtt 7.8 KB
4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/07. Demo - Build and Evaluate a Linear Regression Model.vtt 7.6 KB
1. Preparing Data for Machine Learning with Java/4. Data Cleaning Using Regex and Formatter/5. Demo - Data Cleaning Pipeline.vtt 7.5 KB
1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/8. Demo - Coding for Selenium.vtt 7.5 KB
4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/11. Demo - Assign Roles and Perform Attribute Selection.vtt 7.4 KB
3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/05. Demo - Exploring the Weka Workbench.vtt 7.3 KB
1. Preparing Data for Machine Learning with Java/4. Data Cleaning Using Regex and Formatter/4. Using Regular Expressions in Java.vtt 7.2 KB
3. Implementing Machine Learning Workflow with Weka/3. Implementing Classification Models/4. Demo - Encoding Text Data in Numeric Form.vtt 7.1 KB
4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/03. Demo - Loading and Exploring Data.vtt 7.0 KB
3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/07. Demo - Training and Evaluating a Regression Model.vtt 7.0 KB
2. Exploring Java Machine Learning Environments/5. Implementing a Machine Learning Workflow with Spark MLlib/3. Demo - Data Preprocessing with Spark MLlib.vtt 6.9 KB
1. Preparing Data for Machine Learning with Java/5. Data Transformation/2. Data Transformation Basics.vtt 6.9 KB
3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/08. Demo - Training and Evaluating a Multiple Regression Model.vtt 6.9 KB
3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/5. Demo - Performing Hierarchical Clustering.vtt 6.9 KB
4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/09. Demo - Using a Pretrained Model for Image Segmentation.vtt 6.9 KB
1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/5. Demo - Using the Quartz Scheduler Library.vtt 6.8 KB
2. Exploring Java Machine Learning Environments/4. Implementing a Machine Learning Workflow with DL4J/1. Introduction.vtt 6.5 KB
4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/10. Demo - Evaluate a Model Using Cross-validation.vtt 6.3 KB
4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/04. Demo - Building and Training a Regression Model.vtt 6.2 KB
1. Preparing Data for Machine Learning with Java/6. Data Preparation at Scale/6. Demo - Deploying Beam SDK Pipelines to GCP Dataflow.vtt 6.2 KB
3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/10. Demo - Processing and Saving Processed Data.vtt 6.1 KB
4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/08. Demo - Using a Pretrained Model for Image Classification.vtt 6.0 KB
2. Exploring Java Machine Learning Environments/5. Implementing a Machine Learning Workflow with Spark MLlib/2. Demo - Data Preparation and Loading with Spark MLlib.vtt 5.9 KB
2. Exploring Java Machine Learning Environments/4. Implementing a Machine Learning Workflow with DL4J/5. Demo - Implementing a Twitter Sentiment Classifier with DL4J.vtt 5.9 KB
4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/02. Demo - Getting Set up with a Maven Project.vtt 5.8 KB
4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/05. Demo - Setting up a Repository and Importing Data.vtt 5.7 KB
3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/04. Demo - Environment and Project Setup.vtt 5.6 KB
2. Exploring Java Machine Learning Environments/2. Understanding the Java Machine Learning Ecosystem/3. Demo - Weka Showcase.vtt 5.6 KB
1. Preparing Data for Machine Learning with Java/2. Ingesting Data from Files in Various Formats/4. Ingesting JSON and XML Files.vtt 5.6 KB
1. Preparing Data for Machine Learning with Java/6. Data Preparation at Scale/3. Beam SDK Concepts.vtt 5.5 KB
2. Exploring Java Machine Learning Environments/3. Implementing a Machine Learning Workflow with Weka/1. Introduction.vtt 5.5 KB
4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/10. Demo - Serializing and Deserializing Trained Models.vtt 5.4 KB
2. Exploring Java Machine Learning Environments/3. Implementing a Machine Learning Workflow with Weka/6. Demo - The Full Workflow in One Go with Weka GUI.vtt 5.4 KB
2. Exploring Java Machine Learning Environments/2. Understanding the Java Machine Learning Ecosystem/2. Introduction.vtt 5.4 KB
4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/09. Demo - Perform Attribute Selection.vtt 5.4 KB
3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/06. Demo - Loading and Exploring the Dataset.vtt 5.3 KB
3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/2. Demo - Performing K-means Clustering.vtt 5.2 KB
1. Preparing Data for Machine Learning with Java/4. Data Cleaning Using Regex and Formatter/3. Regular Expressions Overview.vtt 5.2 KB
4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/04. Demo - Download and Setup RapidMiner.vtt 5.2 KB
2. Exploring Java Machine Learning Environments/4. Implementing a Machine Learning Workflow with DL4J/2. Demo - Data Preparation and Loading with DL4J (Part 1 - Setup).vtt 5.2 KB
2. Exploring Java Machine Learning Environments/5. Implementing a Machine Learning Workflow with Spark MLlib/1. Introduction.vtt 5.2 KB
1. Preparing Data for Machine Learning with Java/6. Data Preparation at Scale/2. Distributed Data Pipelines.vtt 5.1 KB
3. Implementing Machine Learning Workflow with Weka/3. Implementing Classification Models/3. Demo - Building and Visualizing a Decision Tree Model.vtt 5.1 KB
4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/06. Demo - Training and Evaluating a Ridge Regression Model.vtt 5.1 KB
4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/11. Demo - Answering Questions with Google BERT.vtt 5.0 KB
3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/12. Demo - Regression Using Support Vector Machines and Multilayer Perceptrons.vtt 5.0 KB
3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/6. Demo - Performing EM Clustering.vtt 5.0 KB
2. Exploring Java Machine Learning Environments/2. Understanding the Java Machine Learning Ecosystem/4. Demo - Deeplearning4j (DL4J) Showcase.vtt 5.0 KB
1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/6. Selenium.vtt 5.0 KB
4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/08. Demo - Train Model on Training Data and Evaluate Using T.vtt 4.9 KB
4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/05. Demo - Evaluating a Regression Model.vtt 4.8 KB
2. Exploring Java Machine Learning Environments/3. Implementing a Machine Learning Workflow with Weka/5. Demo - Evaluation and Visualization with Programmatic Weka.vtt 4.7 KB
1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/3. Task Scheduling.vtt 4.7 KB
4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/05. Demo - Training the Image Classification Model.vtt 4.7 KB
3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/4. Demo - Exploring and Visualizing Data.vtt 4.6 KB
4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/07. Brief Overview of Transfer Learning.vtt 4.6 KB
3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/7. Demo - Serializing Trained Model Parameters.vtt 4.5 KB
4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/01. Introducing DJL.vtt 4.5 KB
4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/01. Introducing JSAT.vtt 4.4 KB
2. Exploring Java Machine Learning Environments/2. Understanding the Java Machine Learning Ecosystem/5. Demo - Spark MLlib Showcase.vtt 4.3 KB
4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/02. Brief Overview of Neural Networks.vtt 4.3 KB
2. Exploring Java Machine Learning Environments/3. Implementing a Machine Learning Workflow with Weka/2. Demo - Data Preparation and Loading with Programmatic Weka.vtt 4.0 KB
4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/03. Introducing RapidMiner.vtt 3.8 KB
1. Preparing Data for Machine Learning with Java/2. Ingesting Data from Files in Various Formats/1. Introduction.vtt 3.8 KB
4. Implementing Machine Learning Workflow with RapidMiner/playlist.m3u 3.7 KB
1. Preparing Data for Machine Learning with Java/6. Data Preparation at Scale/1. Introduction.vtt 3.5 KB
4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/02. Prerequisites and Course Outline.vtt 3.5 KB
3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/02. Prerequisites and Course Outline.vtt 3.3 KB
3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/03. Introducing Weka.vtt 3.3 KB
1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/1. Introduction.vtt 3.1 KB
4. Implementing Machine Learning Workflow with RapidMiner/1. Course Overview/1. Course Overview.vtt 3.1 KB
3. Implementing Machine Learning Workflow with Weka/1. Course Overview/1. Course Overview.vtt 3.1 KB
1. Preparing Data for Machine Learning with Java/4. Data Cleaning Using Regex and Formatter/1. Introduction.vtt 2.9 KB
3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/11. Demo - Evaluating a Model Using Cross Validation.vtt 2.6 KB
2. Exploring Java Machine Learning Environments/2. Understanding the Java Machine Learning Ecosystem/6. Summary.vtt 2.6 KB
2. Exploring Java Machine Learning Environments/playlist.m3u 2.6 KB
4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/08. Demo - Building and Evaluating a Decision Tree Classification Model.vtt 2.5 KB
2. Exploring Java Machine Learning Environments/4. Implementing a Machine Learning Workflow with DL4J/6. Demo - Performance and Evaluation and Visualization with DL4J.vtt 2.5 KB
2. Exploring Java Machine Learning Environments/5. Implementing a Machine Learning Workflow with Spark MLlib/4. Demo - Implementing an Image Classifier with Spark MLlib.vtt 2.5 KB
2. Exploring Java Machine Learning Environments/5. Implementing a Machine Learning Workflow with Spark MLlib/5. Demo - Performance and Evaluation and Visualization with Spark .vtt 2.5 KB
1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/7. Demo - Using the Selenium IDE.vtt 2.5 KB
3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/9. Summary and Further Study.vtt 2.5 KB
2. Exploring Java Machine Learning Environments/1. Course Overview/1. Course Overview.vtt 2.4 KB
4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/12. Summary and Further Study.vtt 2.4 KB
4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/03. Demo - Setting up the Maven Project and Dependencies.vtt 2.3 KB
1. Preparing Data for Machine Learning with Java/2. Ingesting Data from Files in Various Formats/2. What Is Data Preparation.vtt 2.3 KB
1. Preparing Data for Machine Learning with Java/playlist.m3u 2.3 KB
3. Implementing Machine Learning Workflow with Weka/playlist.m3u 2.3 KB
4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/10. Introducing Google BERT.vtt 2.2 KB
1. Preparing Data for Machine Learning with Java/5. Data Transformation/1. Introduction.vtt 2.0 KB
1. Preparing Data for Machine Learning with Java/1. Course Overview/1. Course Overview.vtt 1.7 KB
2. Exploring Java Machine Learning Environments/3. Implementing a Machine Learning Workflow with Weka/3. Demo - Data Preprocessing with Programmatic Weka.vtt 1.7 KB
2. Exploring Java Machine Learning Environments/3. Implementing a Machine Learning Workflow with Weka/4. Demo - Implementing K-means with Programmatic Weka.vtt 1.4 KB
1. Preparing Data for Machine Learning with Java/2. Ingesting Data from Files in Various Formats/6. Summary.vtt 1.2 KB
1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/9. Summary.vtt 1.2 KB
2. Exploring Java Machine Learning Environments/4. Implementing a Machine Learning Workflow with DL4J/7. Summary.vtt 1.0 KB
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