Start your machine learning journey with Python "Go"

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2017-06-07 09:12 Favorites: 1

This article navigation

• -Improve your Python skills 21%
• -Installation of Anaconda30%
• -Basic machine learning skills 34%
• -Learn more about the Python library 48%
• -Explore machine learning 66%

Machine learning is a necessary skill in your resume. Let's briefly summarize some of the steps of using Python for machine learning.

Do you want to know how to start machine learning? In this article, I'll briefly summarize some of the steps to start machine learning using Python. Python is a popular open source programming language and one of the most commonly used languages in artificial intelligence and other related fields of science. Machine learning abbreviation ML is a branch of AI that uses algorithms to learn from data and then make predictions. Machine learning helps us predict the world around us.

From driverless cars to stock market forecasts to online learning, machine learning has been used in almost every area of self-improvement through prediction. Thanks to the practical use of machine learning, it has become one of the most demanding skills in the job market. In addition, using Python to start machine learning is simple because there are a number of online resources, as well as many available Python machine learning libraries.

How do you begin to use Python for machine learning? Let's sum up the process.

Improve your Python skills

Because Python is very popular both in industry and in the scientific community, you don't have to find Python's learning resources. If you're a novice who has never been in touch with Python, you can use online resources such as courses, books, and videos to learn about Python. For example, some of the resources listed below:

• The path to learning Python
• Google Developer Python Course (VIDEO)
• Google's Python Classroom

Installing Anaconda

The next step is to install Anacona. With Anaconda, you will be able to start using Python to explore the world of machine learning. The default installation library for Anaconda contains the tools needed for machine learning.

Basic Machine learning Skills

With some basic Python programming skills, you can start learning some basic machine learning skills. A practical way to learn is to learn a certain skill and start practicing. However, if you want to learn more about this area, you need to be prepared to devote more time to your study.

An effective way to acquire skills is through online courses. Wunda's Coursera machine learning course is a good choice. Other useful online trainings include:

• Python machine Learning: Scikit-learn Tutorials
• Python Practical Machine Learning Tutorial

You can also learn more about this area by watching machine learning videos on the liveedu.tv.

Learn more about Python libraries

When you have a good feeling about Python and machine learning, you can start learning some open source Python libraries. The Scientific Python Library will make it easy to complete some simple machine learning tasks. However, the choice of what library is completely subjective, and many people in the industry have a lot of controversy.

Some of the useful Python libraries include:

• Scikit-learn: An elegant library of machine learning algorithms that can be used for data mining and data analysis tasks.
• TensorFlow: An easy-to-use neural network library.
• Theano: A powerful machine learning library that can help you easily evaluate mathematical expressions.
• Pattern: can help you with natural language processing, data mining, and much more.
• Nilearn: Based on Scikit-learn, it can help you with simple and fast statistical learning.

Explore Machine Learning

With a certain understanding of basic Python, machine learning skills, and the Python library, you can start exploring machine learning. Next, try exploring the Scikit-learn library. A good tutorial is the Scikit-learn profile that Jake Vanderplas wrote.

Then, go to intermediate topics such as introduction to K-means clustering algorithms, linear regression, decision trees, and logistic regression.

Finally, delve into advanced machine learning topics such as vector machines and complex data transformations.

Just as you learn any new skill, the more you practice, the better you will learn. You can better understand machine learning and improve the overall ability to solve problems by practicing different algorithms, using different datasets.

Using Python for machine learning is a great complement to your skills, and there are plenty of free and low-cost online resources to help you. Have you mastered machine learning skills? You can leave a comment below, or submit an article to share your story.

(Picture: opensource.com)

Author Profile:

Dr. Michael J. Garbade is the founder and chief executive officer of San Francisco Liveedu Inc. (livecoding.tv). Livecoding.tv is the world's most advanced live broadcast platform to watch engineers live coding. You can elevate your skills to a new level by watching engineers write websites, mobile apps, and games. Michaelj. Dr. Garbade has a PhD in finance and is a self-taught engineer who likes Python, Django, Sencha Touch and video streaming.

Start your machine learning journey with Python "Go"