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  1. 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

    40
  3. 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
  4. 64. Continuous Distributions The Exponential Distribution | Skyhighes | Data Science

    64. Continuous Distributions The Exponential Distribution | Skyhighes | Data Science

    8
  8. 319. Graphical Representation of Simple Neural Networks | Skyhighes | Data Science

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

    6
  10. 443. Introduction to Terms with Multiple Meanings | Skyhighes | Data Science

    443. Introduction to Terms with Multiple Meanings | Skyhighes | Data Science

    29
  13. 349. Underfitting and Overfitting for Classification | Skyhighes | Data Science

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

    8
  15. 462. Creating Checkpoints while Coding in Jupyter | Skyhighes | Data Science

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

    8
  17. 342. Non-Linearities and their Purpose | Skyhighes | Data Science

    342. Non-Linearities and their Purpose | Skyhighes | Data Science

    11
  18. 306. Addition and Subtraction of Matrices | Skyhighes | Data Science

    306. Addition and Subtraction of Matrices | Skyhighes | Data Science

    17
  19. 321. Common Objective Functions L2-norm Loss | Skyhighes | Data Science

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

    6
  25. 5. What is the difference between Analysis and Analytics | Skyhighes | Data Science

    5. What is the difference between Analysis and Analytics | Skyhighes | Data Science

    25
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