SKILL PATH
Machine learning is used for software applications to help them generate more accurate predictions. It is a type of artificial intelligence being used worldwide and offers high-paying careers. This Skill Path is designed for individuals interested in machine learning but with little programming experience. The Skill Path begins by introducing the basic concepts of the Python programming language and terminology of machine learning, followed by a focus on supervised and unsupervised learning methods. It covers the different types of algorithms used in machine learning and how to select the appropriate algorithm for a given task. The Skill Path also covers data preprocessing, feature selection, and model evaluation. Additionally, it provides an overview of different libraries and frameworks commonly used in machine learning, such as NumPy and pandas. By the end, you’ll have hands-on experience using Python libraries and frameworks for machine learning.
41 hours
261 Lessons
Learning Objectives
Understand the basic concepts of the Python programming language.
Get an overview of common libraries and frameworks used in machine learning.
Understand supervised and unsupervised learning methods.
Learn data preprocessing, feature selection, and model evaluation.
Path Content
Your method is simple, straight to the point and I can practice with it everywhere, even from my phone, that's something I have never had in other learning platforms.
I highly recommend Educative. The courses are well organized and easy to understand.
I prefer Educative courses because they have a nice mix of text & images. I find that with full video courses, it can often be too easy to go into passive learning mode.
I prefer Educative courses because they have a nice mix of text & images. I find that with full video courses, it can often be too easy to go into passive learning mode.
Your method is simple, straight to the point and I can practice with it everywhere, even from my phone, that's something I have never had in other learning platforms.
I highly recommend Educative. The courses are well organized and easy to understand.
I prefer Educative courses because they have a nice mix of text & images. I find that with full video courses, it can often be too easy to go into passive learning mode.