Get your team access to top Uplyrn courses anytime, anywhere.
Overview
Machine learning has become a key industry driver in the global job and opportunity market. In order to stay ahead in careers, machine learning is one of must have skillsets that tech professionals are acquiring as fast as possible. This course is designed by the leading academicians and industry experts to help people learn machine learning and its techniques using Python programming language with many examples and case studies.
Who this course is for
Anyone who wants to learn and build a solid career in artificial intelligence, machine learning, data science field.
What you'll learn
Machine learning techniques
Supervised machine learning
Unsupervised machine learning
Semi-supervised machine learning
Reinforcement learning
Linear regression with Python
Solving classification problems with discriminant analysis with a case study
Logistic regression with Python
Decision tree with Python
Solving unsupervised learning problems with cluster analysis
K-means clustering with Python
Hierarchical clustering
Application of AI in cyber security
Application of AI in FinTech
Requirements
You will need to have a computer or a mobile handset with an internet connection and a lot of aspirations to master machine learning.
Overview
Machine learning has become a key industry driver in the global job and opportunity market. In order to stay ahead in careers, machine learning is one of must have skillsets that tech professionals are acquiring as fast as possible. This course is designed by the leading academicians and industry experts to help people learn machine learning and its techniques using Python programming language with many examples and case studies.
Who this course is for
Anyone who wants to learn and build a solid career in artificial intelligence, machine learning, data science field.
What you'll learn
Requirements
You will need to have a computer or a mobile handset with an internet connection and a lot of aspirations to master machine learning.
Course Content
9 Sections 26 Lectures 3h 38m total length
All Comments