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

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

    9
  2. 374. MNIST Preprocess the Data - Shuffle and Batch | Skyhighes | Data Science

    374. MNIST Preprocess the Data - Shuffle and Batch | Skyhighes | Data Science

    9
  3. 1. A Practical Example What You Will Learn in This Course | Skyhighes | Data Science

    1. A Practical Example What You Will Learn in This Course | Skyhighes | Data Science

    47
  5. 449. Analyzing the Reasons for Absence | Skyhighes | Data Science

    449. Analyzing the Reasons for Absence | Skyhighes | Data Science

    11
  6. 442. Checking the Content of the Data Set | Skyhighes | Data Science

    442. Checking the Content of the Data Set | Skyhighes | Data Science

    2
  7. 475. Selecting the Inputs for the Logistic Regression | Skyhighes | Data Science

    475. Selecting the Inputs for the Logistic Regression | Skyhighes | Data Science

    2
  8. 517. pandas DataFrames - Indexing with .loc[] | Skyhighes | Data Science

    517. pandas DataFrames - Indexing with .loc[] | Skyhighes | Data Science

    21
  9. 515. Data Selection in pandas DataFrames | Skyhighes | Data Science

    515. Data Selection in pandas DataFrames | Skyhighes | Data Science

    14
  10. 513. Introduction to pandas DataFrames - Part II | Skyhighes | Data Science

    513. Introduction to pandas DataFrames - Part II | Skyhighes | Data Science

    18
  11. 509. Parameters and Arguments in pandas | Skyhighes | Data Science

    509. Parameters and Arguments in pandas | Skyhighes | Data Science

    14
  13. 501. Introduction to Nested For Loops | Skyhighes | Data Science

    501. Introduction to Nested For Loops | Skyhighes | Data Science

    11
  14. 297. Understanding Differences between Multinomial and Bernouilli Skyhighes | Data Science

    297. Understanding Differences between Multinomial and Bernouilli Skyhighes | Data Science

    6
  15. 286. Algorithm recommendation recommendation engine | Skyhighes | Data Science

    286. Algorithm recommendation recommendation engine | Skyhighes | Data Science

    7
  16. 508. Working with Methods in Python - Part II | Skyhighes | Data Science

    508. Working with Methods in Python - Part II | Skyhighes | Data Science

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

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

    8
  18. 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
  19. 361. Learning Rate Schedules Visualized | Skyhighes | Data Science

    361. Learning Rate Schedules Visualized | Skyhighes | Data Science

    16
  20. 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
  21. 242. Binary Predictors in a Logistic Regression | Skyhighes | Data Science

    242. Binary Predictors in a Logistic Regression | Skyhighes | Data Science

    5
  22. 490. Deploying the 'absenteeism_module' - Part I | Skyhighes | Data Science

    490. Deploying the 'absenteeism_module' - Part I | Skyhighes | Data Science

    5
  23. 481. Standardizing only the Numerical Variables | Skyhighes | Data Science

    481. Standardizing only the Numerical Variables | Skyhighes | Data Science

    4
  24. 474. Creating the Targets for the Logistic Regression | Skyhighes | Data Science

    474. Creating the Targets for the Logistic Regression | Skyhighes | Data Science

    3
  25. 239. Understanding Logistic Regression Tables | Skyhighes | Data Science

    239. Understanding Logistic Regression Tables | Skyhighes | Data Science

    3