Here’s How to Learn Python for Machine Learning

If you are new to machine learning, you have to choose a programming language to learn machine learning and implement it on data. Python is one of the most preferred programming languages for machine learning. So if you want to understand how to learn Python for machine learning, this article is for you. In this article, I will take you through how to learn Python for machine learning step by step.

Here’s How to Learn Python for Machine Learning

Learn the Fundamentals of Python

Before starting with machine learning, you should know the basics of the programming language you will use for machine learning. So learn the basics of Python first, and if this is your first programming language, you should spend some time improving your programming fundamentals and problem-solving skills. As Python is a popular programming language, you can easily find many free and paid resources on the internet to learn Python. If you want a video tutorial to learn Python, you can follow this video, and if you prefer to follow a book, you can check out this book.

Learn Python Libraries for Machine Learning

After learning the fundamentals of Python, you can move to learn Python for machine learning. To learn Python for machine learning, you have to learn some libraries and frameworks that are helpful and used by professionals for solving machine learning problems. So below are all the libraries that you need to learn for machine learning:

  1. NumPy
  2. Pandas
  3. Matplotlib
  4. Seaborn
  5. Scikit-Learn
  6. Tensorflow
  7. PyTorch

These Python libraries are so popular that you will get a dedicated tutorial on each of these libraries on every platform based on data science and machine learning. I will recommend you to learn about these libraries from their official documentation. If you want to follow a book for learning Python for machine learning, you can follow the books mentioned below:

  1. Python Data Science Handbook
  2. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow
  3. Deep Learning with PyTorch

Practice

After learning the fundamentals of Python and all the Python libraries you need for machine learning, you should start working on solving case studies and practice projects to implement everything you have learned. You can find some case studies and projects solved and explained using Python from here.

Summary

So for learning Python for machine learning, start with the fundamentals of Python, then move to the essential Python libraries for machine learning, and then work on case studies and projects to practice your problem-solving skills. I hope you liked this article on the steps for learning Python for machine learning. Feel free to ask valuable questions in the comments section below.

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Aman Kharwal

Coder with the ♥️ of a Writer || Data Scientist | Solopreneur | Founder

Articles: 1297

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