This document provides an introduction to Python programming for machine learning. It discusses what Python is, why it is useful for ML, and how to get started with the PyCharm IDE. It then covers basic Python concepts like variables, data types, operators, functions, conditionals, loops, lists, strings, and dictionaries. Examples are provided throughout to demonstrate different Python syntax and functions. The goal is to equip readers with foundational Python knowledge to begin working on ML and deep learning projects.

1. Fatma Intissar CHAHBAR
• Networks & telecommunicaton engineer
• Data Analyst
• Certified Tensorflow Developer

2. Intro To
Machine
Learning

3. What is AI?

4. Do what human Do

5. Machine Learning (ML)

6. Example

7. Deep Learning

8. Deep Learning VS Machine Learning

9. Summary

10. Hello Python
Using Pycharm

11. Python is a programming language that supports the creation of a wide
range of applications. Developers regard it as a great choice for Machine
Learning, and Deep Learning projects
What is Python !
Why python
• It has a huge number of libraries and frameworks
• Simplicity
• The massive online support
• Fast development
• Visualization tools

12. PyCharm is an IDE (Integrated Development Environment) made specifically
for use with Python. You’ll need it for this workshop. You can also use
Anaconda (Jupyter Notebook) , Google Colab , Kaggle … etc
What is Pycharm !

13. Hello Python!

14. Hello Python!

15. Variable assignement :Here we create a variable called num and assign it the value of 0
using =, which is called the assignement operator
Aside: if you’ve programmed in certain other languages (like java or C++), you
might be noticing some things Python doesn’t require us to do here:
●We don’t need to « declare » num before assigning to it
●We don’t need to tel Python what type of value num is going to refer to .In fact, we
can even go on to reassign num to refer a different sort of thing like a string or a
boolean.
Variable assignement

16. Functions

17. Function call

18. Numbers and Arithmetic in python
“Number” is a fine informal name for the kind of thing, but if we wanted to be more
technical, we could ask python how it would describe the type of thin that num is :

19. Operators

20. Examples
It always give us a float.
The // operator give us the result that’s rounded down to the next integer.

21. The arithmetic we learned in primary school coventions about the order in which operations are
evaluated.
Some remember these by a mnemonic such as PEMDAS (Parentheses, Exponents, Multiplication/Division,
Addition/Subtraction).
Python follows similar rules about which calculations to perform first.They’re mostly pretty intuitive.
Order of Operations

22. Examples

23. Built-in functions
Built in functions for working with numbers .
Min and max return the minimum and the maximum of their arguments, respectively…

24. Functions which convert their arguments.

25. Functions and getting help.

26. Common Pitfall

27. Help(print)

28. Any Questions !!!

29. Defining functions

30. Functions that don’t return

31. Examples

32. Functions applied to function

33. Boolean & Conditions

34. Boolean & Conditions

35. Examples

36. Comparaison
But Sometimes they can be tricky , like this second examples.

37. Examples

38. Conditionals

39. Boolean Conversion

40. Listes

41. Lists
Lists in Python represent orders sequence of values.Here is an example of how to create the:
We can put other type of things in lists:
We can even make a list of lists

42. What is the next closest Planet:

43. Slicing
What are the three first planets? We can answer this question using slicing:
Planets[0:3] is our way of asking for the elements of planets starting from index 0 and continuing up
to but not including index 3
The starting and ending indices are both optional. If I leave out the start index, it’s assumed to be
0. So I could rewrite the expression above as :

44. Loops

47. Strings

49. Scape Sequence

51. Dictionaries

54. Questions!!

55. Thank You