Machine Learning Using Python | BSH
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1
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1. Introduction to the Course
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2. Human learning and it's types
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3. Machine learning and it's types
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4. Process of Machine Learning
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5. Applications of machine learning
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2
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6. Basic data types
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7. Data exploration
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8. Data exploration (continued)
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9. Data issues and remediation
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10. Issues in machine learning
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3
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11. Getting started with Python
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12. Basic Python commands
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13. Basic Python commands (continued)
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14. Functions
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15. Operators
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16. Conditional (IF) Statement
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17. FOR Loops
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18. WHILE Loops
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19. Libraries - os, numpy, pandas, matplotlib
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20. numpy
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21. pandas
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4
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22. What is a model
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23. Selecting a model
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24. Training model - Holdout Method
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25. Model performance evaluation - Classification
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5
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26. Classification algorithm - K-Nearest Neighbour 1
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27. Classification algorithm - K-Nearest Neighbour 2
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28. Classification algorithm - K-Nearest Neighbour 3
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29. Classification algorithm - K-Nearest Neighbour 4
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30. Classification algorithm - K-Nearest Neighbour 5
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31. Regression