Machine Learning
Machine learning (ML) provides the capability for computers to learn from data. This course enables the student with an introduction to various different types and applications of ML. Topics include, supervised learning, unsupervised learning, reinforcement learning, statistical learning, vector support machines, neural networks, fuzzy inference systems, data clustering and transformations, decision tree learning, and data mining, etc.
Skills you will gain
Evaluate different types of machines learning.
Assess machine learning capabilities to determine how they will be applicable to the workplace.
Analyze the leader’s role in recognizing machine learning as an important subset of AI.
What will you learn?
Evaluate supervised, unsupervised, and reinforcement learnings
Distinguish between machine and statistical learning.
Summarize support vector machines.
Summarize artificial neural networks.
Summarize artificial neural networks.
Appraise the need for data clustering and data transformations.
Summarize decision tree learning.
Summarize data mining.
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