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  1. 298. Machine Learning with Naïve Bayes (First Attempt) | Skyhighes | Data Science

    298. Machine Learning with Naïve Bayes (First Attempt) | Skyhighes | Data Science

    17
  2. 293. Overcome Imbalanced Data in Machine Learning | Skyhighes | Data Science

    293. Overcome Imbalanced Data in Machine Learning | Skyhighes | Data Science

    16
  3. 361. Learning Rate Schedules Visualized | Skyhighes | Data Science

    361. Learning Rate Schedules Visualized | Skyhighes | Data Science

    16
  6. 473. Exploring the Problem with a Machine Learning Mindset | Skyhighes | Data Science

    473. Exploring the Problem with a Machine Learning Mindset | Skyhighes | Data Science

    32
  8. 322. Common Objective Functions Cross-Entropy Loss | Skyhighes | Data Science

    322. Common Objective Functions Cross-Entropy Loss | Skyhighes | Data Science

    3
  9. 321. Common Objective Functions L2-norm Loss | Skyhighes | Data Science

    321. Common Objective Functions L2-norm Loss | Skyhighes | Data Science

    3
  11. 319. Graphical Representation of Simple Neural Networks | Skyhighes | Data Science

    319. Graphical Representation of Simple Neural Networks | Skyhighes | Data Science

    3
  12. 318. The Linear model with Multiple Inputs and Multiple Outputs | Skyhighes | Data Science

    318. The Linear model with Multiple Inputs and Multiple Outputs | Skyhighes | Data Science

    3
  13. 317. The Linear Model with Multiple Inputs | Skyhighes | Data Science

    317. The Linear Model with Multiple Inputs | Skyhighes | Data Science

    3
  14. 316. The Linear Model (Linear Algebraic Version) | Skyhighes | Data Science

    316. The Linear Model (Linear Algebraic Version) | Skyhighes | Data Science

    3
  15. 313. Introduction to Neural Networks | Skyhighes | Data Science

    313. Introduction to Neural Networks | Skyhighes | Data Science

    3
  17. 432. What are Data, Servers, Clients, Requests, and Responses | Skyhighes | Data Science

    432. What are Data, Servers, Clients, Requests, and Responses | Skyhighes | Data Science

    5
  18. 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

    5
  19. 485. Saving the Model and Preparing it for Deployment | Skyhighes | Data Science

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

    6
  20. 483. Backward Elimination or How to Simplify Your Model | Skyhighes | Data Science

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

    6
  22. 433. What are Data Connectivity, APIs, and Endpoints | Skyhighes | Data Science

    433. What are Data Connectivity, APIs, and Endpoints | Skyhighes | Data Science

    8
  23. 422. The Importance of Working with a Balanced Dataset | Skyhighes | Data Science

    422. The Importance of Working with a Balanced Dataset | Skyhighes | Data Science

    8
  24. 409. MNIST What is the MNIST Dataset | Skyhighes | Data Science

    409. MNIST What is the MNIST Dataset | Skyhighes | Data Science

    3