With the growth in technology, interest in the field of machine learning is continuously accelerating. Machine learning provides the ability to systems to learn from data, identify patterns and make decisions. It analyses huge and complex data and offers faster predictions and more accurate results. The concept of machine learning is not new; however, it gained momentum in the 21st century. Machine learning is being applied to different domains such as finance, retail, automobiles to enable services such as online recommendation, fraud detection, and self-driving car. This course is a comprehensive guide to machine learning with Python. It helps in creating a successful machine-learning application with Python and the scikit-learn library.
Learning Objectives
Fundamental to Machine Learning ,introduction to Python ,describe Linear regression and Logistic regression, discuss Neural network, illustrate Clustering and Classification,describe Support vector machine and Association rule learning.
Framework Connections
The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):
Competency Areas
Work Roles
Feedback
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