A 3 day Python Bootcamp for ML Beginners
Tags: Hackernoon Top Story, Bootcamp, Data Science, Machine Learning, Python

Python Basic(Day-01)

We are going to get familiar with Python. In Day-01 we was covered the basic portion of Python which can be very useful for Machine Learning or Data Science.

What is python?

Python is developed by Guido van Rossum. Guido van Rossum started implementing Python in 1989. Python is a general-purpose, object-oriented and open source computer programming language, it is a high-level, human-readable and a corresponding set of software tools and libraries.

Interesting fact: Python is named after the comedy television show Monty Python’s Flying Circus. It is not named after the Python snake.

Features of Python programming language:

Readable: Python is a very readable language.

2. Easy to Learn: Learning python is easy as this is a expressive and high level programming language, which means it is easy to understand the language and thus easy to learn.

3. Cross platform: Python is available and can run on various operating systems such as Mac, Windows, Linux, Unix etc. This makes it a cross platform and portable language.

4. Open Source: Python is a open source programming language.

5. Large standard library: Python comes with a large standard library that has some handy codes and functions which we can use while writing code in Python.

6. Free: Python is free to download and use. This means you can download it for free and use it in your application. See: Open Source Python License

7. Supports exception handling: If you are new, you may wonder what is an exception? An exception is an event that can occur during program exception and can disrupt the normal flow of program. Python supports exception handling which means we can write less error prone code and can test various scenarios that can cause an exception later on.

8. Advanced features: Supports generators and list comprehensions. We will cover these features later.

9. Automatic memory management: Python supports automatic memory management which means the memory is cleared and freed automatically. You do not have to bother clearing the memory.

How to Install Python:

You can install Python on any operating system such as Windows, Mac OS X, Linux/Unix and others.

To install the Python on your operating system, go to this link. You will see a screen like this.

This is the official Python website and it will detect the operating system and based on that it would recommend you to download Python. Here I am using Windows so it gave me the download options for Python 2 and Python 3 for Windows. I would recommend you to download the latest version of Python 3 (Python 3.7.2 in the screenshot).

Installation steps are pretty simple. You just have to accept the agreement and finish the installation.

Python basic topics:

We was covered the basic portion of Python.Basic parts below here-

Variables and Maths Operations Type Casting String List Tuples Sets Dictionaries User input

Everyone can learn this from our notebook.Notebook below here —

Python Intermediate(Day-02)

We are going to get familiar with Python. In Day-02 We will focus on 9 python functions commonly used for machine learning.which can be very useful for Machine Learning or Data Science.

Python Intermediate topics:

We will focus on 9 python functions commonly used for machine learning.Intermediate parts below here —

if-Elif-Else For Loop While Loop Functions Lambda expressions List Comprehensions Errors and Exceptions Handling Math module Map

Everyone can learn this from our notebook.Notebook below here —

ML or Data Science Basic Packages(Day-03)

We are going to get familiar with Python. In Day-03 we will focus on ML or Data Science basic packages of Python which can be very useful for Machine Learning or Data Science.

ML or Data Science Packages topics:

we will focus on ML or Data Science basic packages of Python.ML or Data Science packages parts below here —

Numpy Pandas Matplotlib Seaborn Scikit-learn

Everyone can learn this topics with us.Just need wait and everyone will be get this topics in Github. Github repository link below —

Conclusion

Thanks for reading this article. If you have any suggestion feel free to reach me in the comment or sent mail or connect on LinkedIn. Stay in touch for more update. Thank you. 😎

My working partner Richa Yadav. She is awesome friend of me. If you have any suggestion feel free to reach her in the comment or connect on LinkedIn.