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  1. 377. MNIST Select the Loss and the Optimizer | Skyhighes | Data Science

    377. MNIST Select the Loss and the Optimizer | Skyhighes | Data Science

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  2. 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
  5. 271. Traditional data science methods and the role of ChatGPT | Skyhighes | Data Science

    271. Traditional data science methods and the role of ChatGPT | Skyhighes | Data Science

    3
  6. 322. Common Objective Functions Cross-Entropy Loss | Skyhighes | Data Science

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

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

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

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

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

    3
  10. 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
  11. 317. The Linear Model with Multiple Inputs | Skyhighes | Data Science

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

    4
  12. 316. The Linear Model (Linear Algebraic Version) | Skyhighes | Data Science

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

    4
  13. 313. Introduction to Neural Networks | Skyhighes | Data Science

    313. Introduction to Neural Networks | Skyhighes | Data Science

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

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

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  16. 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
  17. 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
  18. 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
  20. 433. What are Data Connectivity, APIs, and Endpoints | Skyhighes | Data Science

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

    8
  21. 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
  22. 409. MNIST What is the MNIST Dataset | Skyhighes | Data Science

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

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  23. 288. Using ChatGPT for ethical considerations | Skyhighes | Data Science

    288. Using ChatGPT for ethical considerations | Skyhighes | Data Science

    9