Machine Learning with Python Basics (For Beginners)

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

Notes:

1. You will learn the basics of Machine Learning.

2. You will learn the basics of python.

3. You will need to set up Anaconda.

4. You will need to setup python & PyCharm

5. This course is considered the first step in Machine Learning.

6. You can ask anytime.

7. No Programming Experience is Needed for this course.

8. Python for Data Science and Machine Learning is a great course that you can take to learn the implementation of ML models in Python.

9. This course is considered step one in Machine Leaning, You will learn the concept of Machine Learning with python basics.