Source: analyticsindiamag.com

Python is one of the most preferred high-level programming languages, which is being increasingly utilised in data science and in designing complex machine learning algorithms. In one of our articles, we discussed why one should learn the Python programming language for data science and machine learning.

In this article, we list down the top 9 free resources to learn Python for Machine Learning.

1| Google’s Python Class

About: This is a free class provided by the developers at Google. It includes written materials, lecture videos, and lots of code exercises to practice Python coding. The first exercises work on basic Python concepts like strings and lists, building up to the later exercises which are full programs dealing with text files, processes, and Http connections.

2| Introduction to Data Science using Python

About: In this course, you will understand the basics of data science and analytics as well as how to use Python and scikit-learn. The course will show you what data science is and how is it used. You will go through commonly used terms and write some code in Python as well.   

3| Data Science, Machine Learning, Data Analysis, Python & R

About: This course has been designed by data scientists to help you learn complex theory, algorithms, and Python libraries. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of data science. The course includes both Python and R and is also packed with practical exercises that are based on real-life examples.

4| MatPlotLib with Python

About: This course has been designed for those who want to learn a variety of ways to visually display data. With over 58 lectures and 6 hours of content, this course covers almost every major chart that Matplotlib is capable of providing. Intended for students who already have a basic understanding of Python. You will take a step-by-step approach to create line graphs, scatter plots, stack plots, bar charts, 3D lines, 3D wireframes, 3D bar charts, 3D scatter plots, geographic maps, live-updating graphs, and much more. On completion of this course, you will not only have gained a deep understanding of the options available for visualising data but also know how to create well presented, visually appealing graphs.  

5| Data Science with Analogies, Algorithms and Solved Problems

About: This course will help you learn complex theory, algorithms and coding libraries in a simple way. With every tutorial, you will gain new skills and enhance your understanding of this field. It includes a brief introduction to Python and its libraries and how to implement this language in machine learning. 

6| Machine Learning In Python

About: In this e-book, you will learn essential techniques of machine learning in predictive analysis using Python programming language. The topic includes predictive model building, writing ensemble methods using Python, understanding and working with data and much more. 

7| Machine Learning With Python

About: This tutorial provides a quick introduction to Python and its libraries like NumPy, SciPy, pandas, Matplotlib, and explains how it can be applied to develop machine learning algorithms that solve real-world problems. The tutorial starts with an introduction to machine learning and the Python language and shows you how to set up Python and its packages. It further covers all important concepts such as exploratory data analysis, data preprocessing, feature extraction, data visualisation, clustering, classification, regression and model performance evaluation.

8| Modern Machine Learning in Python

About: Here, you will learn the basics of Python and machine learning and why Python is needed for performing machine learning tasks. It includes an introduction to machine learning, why Python is becoming the central tool for data scientists, alternatives to Python in data science and other such.

9| Python for Data Science

About: This free Python course provides a beginner-friendly introduction to Python for Data Science. This will kickstart your learning of Python for data science, as well as programming in general. Upon its completion, you’ll be able to write your own Python scripts and perform basic hands-on data analysis using Jupyter-based lab environment.