Machine learning is one of the most anticipated skills you can add to your resume. Do you know what do you need to start with machine learning? In this guide, we will discuss how to use Python to get started with machine learning.

Python is one of the well-known open source languages. It is also used in various scientific fields like artificial intelligence (AI). On the other side, machine learning (ML) is the field of AI which learns from data with algorithms and makes predictions. Machine Learning is very helpful to predict our environment.

From online learning to stock market predictions and self-driving automobiles, machine learning plays a vital role in virtually every field where prediction is required for improvement. It is one of the most anticipated skills these days, thanks to its huge usage.

It is also very easy to get started with machine learning and Python as you can find as lot of libraries for Python machine learning and online resources. Here’s how to get started with Python machine learning.

Improve your Python Skills

Python is a very popular and widely used language, both in scientific and industrial facilities. So, there is no lack of resources to learn Python. You can learn Python with various online materials, including, books, courses, and videos if you are an absolute beginner.

Install Anaconda

Anaconda is another great way to explore the world of machine learning using Python. The package of Anaconda covers all the tools you need to get into the depth of machine learning.

Basic skills in machine learning

With some of the basic skills in Python programming, you can easily learn some of the basic knowledge in machine learning. To get started, it is enough if you have a sensible approach. If you want to dig deeper into the subject matter, you need to invest hundreds of hours.

Learn about Python Packages

After gaining proper understanding for machine learning and Python programming, be sure to learn open source Python. You can learn to complete some of the basic ML tasks with scientific Python libraries. Choosing these libraries is absolutely subjective and it is much talked about by many people in the job market.

Here are some of the best Python libraries to look for –

• Scikit-learn – It is a neat machine learning library which can be used widely fore data analysis and data mining.
• Theano – It is a very effective machine learning library to evaluate expressions.
• Tensorflow – It is a very user-friendly neural network library.
• Nilearn – Based on Scikit-learn, Nilearn is helpful for fast and simple statistical learning.
• Pattern – It is helpful in data mining, Natural Learning processing, and even more.

Final Thoughts

With some basic knowhow of machine learning skills, Python, and Python libraries, you can get started.

Jump into topics like linear regression, intro to K-means clustering, logical regression, and decision trees.

Finally, you can venture into advanced topics of machine learning, such as complex data transformation and vector machines. The more you practice, the better.