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  1. 488. Preparing the Deployment of the Model through a Module | Skyhighes | Data Science

    488. Preparing the Deployment of the Model through a Module | Skyhighes | Data Science

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  2. 485. Saving the Model and Preparing it for Deployment | Skyhighes | Data Science

    485. Saving the Model and Preparing it for Deployment | Skyhighes | Data Science

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  3. 483. Backward Elimination or How to Simplify Your Model | Skyhighes | Data Science

    483. Backward Elimination or How to Simplify Your Model | Skyhighes | Data Science

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  4. 381. Business Case Exploring the Dataset and Identifying Predictors | Skyhighes | Data Science

    381. Business Case Exploring the Dataset and Identifying Predictors | Skyhighes | Data Science

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  5. 371. MNIST Importing the Relevant Packages and Loading the Data | Skyhighes | Data Science

    371. MNIST Importing the Relevant Packages and Loading the Data | Skyhighes | Data Science

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  6. 465. Analyzing the Dates from the Initial Data Set | Skyhighes | Data Science

    465. Analyzing the Dates from the Initial Data Set | Skyhighes | Data Science

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  7. 462. Creating Checkpoints while Coding in Jupyter | Skyhighes | Data Science

    462. Creating Checkpoints while Coding in Jupyter | Skyhighes | Data Science

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  10. 358. Problems with Gradient Descent | Skyhighes | Data Science

    358. Problems with Gradient Descent | Skyhighes | Data Science

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  11. 406. Basic NN Example with TF Loss Function and Gradient Descent | Skyhighes | Data Science

    406. Basic NN Example with TF Loss Function and Gradient Descent | Skyhighes | Data Science

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  12. 405. Basic NN Example with TF Inputs, Outputs, Targets, Weights, Biases | Skyhighes | Data Science

    405. Basic NN Example with TF Inputs, Outputs, Targets, Weights, Biases | Skyhighes | Data Science

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  13. 389. Business Case Setting an Early Stopping Mechanism | Skyhighes | Data Science

    389. Business Case Setting an Early Stopping Mechanism | Skyhighes | Data Science

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  14. 398. An Overview of non-NN Approaches | Skyhighes | Data Science

    398. An Overview of non-NN Approaches | Skyhighes | Data Science

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  15. 479. Creating a Summary Table with the Coefficients and Intercept | Skyhighes | Data Science

    479. Creating a Summary Table with the Coefficients and Intercept | Skyhighes | Data Science

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  16. 477. Splitting the Data for Training and Testing | Skyhighes | Data Science

    477. Splitting the Data for Training and Testing | Skyhighes | Data Science

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  17. 233. Introduction to Logistic Regression | Skyhighes | Data Science

    233. Introduction to Logistic Regression | Skyhighes | Data Science

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  19. 337. Customizing a TensorFlow 2 Model | Skyhighes | Data Science

    337. Customizing a TensorFlow 2 Model | Skyhighes | Data Science

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  20. 335. Outlining the Model with TensorFlow 2 | Skyhighes | Data Science

    335. Outlining the Model with TensorFlow 2 | Skyhighes | Data Science

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  21. 331. TensorFlow Outline and Comparison with Other Libraries | Skyhighes | Data Science

    331. TensorFlow Outline and Comparison with Other Libraries | Skyhighes | Data Science

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  24. 349. Underfitting and Overfitting for Classification | Skyhighes | Data Science

    349. Underfitting and Overfitting for Classification | Skyhighes | Data Science

    3