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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/Ex_Files_Machine_Learning_Algorithms/Exercise Files/GB_model.pkl |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/Ex_Files_Machine_Learning_Algorithms/Exercise Files/test_features.csv |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/01 - The power of algorithms in machine learning.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/01 - The power of algorithms in machine learning.mp4 |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/02 - What you should know.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/02 - What you should know.mp4 |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/03 - What tools you need.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/03 - What tools you need.mp4 |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/04 - Using the exercise files.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/04 - Using the exercise files.mp4 |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/05 - Defining model vs. algorithm.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/06 - Process overview.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/06 - Process overview.mp4 |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/07 - Clean continuous variables.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/08 - Clean categorical variables.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/09 - Split into train, validation, and test set.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/09 - Split into train, validation, and test set.mp4 |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/10 - What is logistic regression.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/10 - What is logistic regression.mp4 |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/11 - When should you consider using logistic regression.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/12 - What are the key hyperparameters to consider.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/13 - Fit a basic logistic regression model.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/14 - What is Support Vector Machine.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/15 - When should you consider using SVM.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/16 - What are the key hyperparameters to consider.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/17 - Fit a basic SVM model.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/18 - What is a multi-layer perceptron.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/18 - What is a multi-layer perceptron.mp4 |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/19 - When should you consider using a multi-layer perceptron.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/20 - What are the key hyperparameters to consider.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/21 - Fit a basic multi-layer perceptron model.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/22 - What is Random Forest.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/22 - What is Random Forest.mp4 |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/23 - When should you consider using Random Forest.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/24 - What are the key hyperparameters to consider.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/25 - Fit a basic Random Forest model.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/26 - What is boosting.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/27 - When should you consider using boosting.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/28 - What are the key hyperparameters to consider boosting.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/29 - Fit a basic boosting model.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/30 - Why do you need to consider so many different models.mp4 |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/31 - Conceptual comparison of algorithms.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/31 - Conceptual comparison of algorithms.mp4 |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/32 - Final model selection and evaluation.en.srt |
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[Lynda] Applied Machine Learning - Algorithms/[Lynda] Applied Machine Learning - Algorithms/33 - Next steps.en.srt |
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