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

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

    11
  3. 462. Creating Checkpoints while Coding in Jupyter | Skyhighes | Data Science

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

    8
  5. 306. Addition and Subtraction of Matrices | Skyhighes | Data Science

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

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

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

    6
  14. 205. What is sklearn and How is it Different from Other Packages | Skyhighes | Data Science

    205. What is sklearn and How is it Different from Other Packages | Skyhighes | Data Science

    12
  15. 32. Solving Variations with Repetition | Skyhighes | Data Science

    32. Solving Variations with Repetition | Skyhighes | Data Science

    12
  17. 287. Ethical principles in data and AI utilization | Skyhighes | Data Science

    287. Ethical principles in data and AI utilization | Skyhighes | Data Science

    14
  18. 144. Numbers and Boolean Values in Python | Skyhighes | Data Science

    144. Numbers and Boolean Values in Python | Skyhighes | Data Science

    11
  19. 293. Overcome Imbalanced Data in Machine Learning | Skyhighes | Data Science

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

    18
  21. 344. Activation Functions Softmax Activation | Skyhighes | Data Science

    344. Activation Functions Softmax Activation | Skyhighes | Data Science

    7
  23. 294. Loading the Dataset and Preprocessing | Skyhighes | Data Science

    294. Loading the Dataset and Preprocessing | Skyhighes | Data Science

    14
  24. 351. Training, Validation, and Test Datasets | Skyhighes | Data Science

    351. Training, Validation, and Test Datasets | Skyhighes | Data Science

    12
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