/ML-notes-course

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Machine Learning Course notes

Here, you can see some notes about Machine Learning course by Analytics Vidhya. Hope you find useful.

You will be going through:

  1. Data Structure
  2. List []
  3. Tuples ()
  4. Sets and Dictionaries {}
  5. String Manipulation
  6. Functions
  7. Modules, Packages and Standard Libraries
  8. Reading Data in Python
  9. Preprocessing, Subsetting and Modifying pandas DataFrame
  10. Machine Learning Lifecycle
  11. Importance of Stats and Exploratory Data Analysis (EDA)
  12. Build your First Predictive Model
  13. Evaluation Metrics
  14. Processing data
  15. Build Your Fisrt ML Model
  16. Selecting the Rigth Model
  17. Linear Models
  18. Decision Tree
  19. Feature Engineering

Some models you will learn in this course notes:

  1. KNN
  2. Linear Regression
  3. Logistic Regression
  4. Decision Tree

Most libraries used in this course:

  1. Numpy
  2. Pandas
  3. Matplotlib
  4. Scikit-Learn
  5. Seaborn
  6. Featuretools