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Machine Learning with Python Basics (For Beginners)

Machine Learning with Python Basics (For Beginners)

The reader can be a beginner or an advanced learner. This tutorial has been prepared for the students as well as professionals to ramp up quickly. Learn the Basics of Machine Learning with Python (First Step For Beginners)

What you'll learn

  • You Will learn basic concept of Machine Learning, Types of Machine Learning
  • You Will learn basic concept of Linear Regression With One Variable & Multiple
  • You Will learn basic concept of Logistic Regression
  • You Will learn basic concept of Regularization (Linear and Logistic Regression)
  • You Will learn basic concept of Neural Network
  • Machine Learning Projects

Steps of Machine Learning that you Will learn:

  1. Import the data.
  2. Split data into Training & Test.
  3. Create a Model.
  4. Train The Model.
  5. Make Predictions.
  6. Evaluate and improve.

Machine Learning Course Contents:

  1. What is Machine Learning - Types of Machine Learning (Supervised & Unsupervised).
  2. Linear Regression with One Variable.
  3. Linear Regression with One Variable (Cost Function - Gradient Descent).
  4. Linear Regression with Multiple Variable.
  5. Logistic Regression (Classification).
  6. Logistic Regression (Cost Function - Gradient Descent).
  7. Logistic Regression (Multiclass).
  8. Regularization Overfitting.
  9. Regularization (Linear and Logistic Regression).
  10. Neural Network Overview.
  11. Neural Network (Cost Function).
  12. Advice for Applying Machine Leaning.
  13. Machine Learning Project 1
  14. Machine Learning Project 2

Python Basics Course Contents:

  1. How to print
  2. Variables
  3. Receive Input from User
  4. Type Conversion
  5. String
  6. Formatted String
  7. String Methods
  8. Arithmetic Operations
  9. Math Functions
  10. If Statement
  11. Logical Operators
  12. Comparison Operators
  13. While
  14. For Loops
  15. Nested Loops
  16. List
  17. 2D List
  18. List Methods
  19. Tuples
  20. Unpacking
  21. Dictionaries
  22. Functions
  23. Parameters
  24. Keyword Arguments
  25. Return Statement
  26. Try - Except
  27. Comments
  28. Classes

Online Course CoupoNED based Analytics Education Company and aims at Bringing Together the analytics companies and interested Learners.