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Fundamentals of Machine Learning
Fundamentals of Machine Learning  - online training course
 
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3-hour Online Course by Asha Saxena
Single-user access license
Our Price: $295.00

Product Code: SC-10-A


Course Exam [Add $80.00]

Description Course Outline Exam Details
 

Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. It is pervasive today in everyday life from recommendation engines to practical speech recognition, web searches to advanced GPS systems. Businesses are taking advantage of machine learning in creating advanced solutions to serve their customer segments.

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Just as humans learn by example, machine learning algorithms learn by example. Machine learning allows us to both learn from the past to inform the future and give our data a voice. There are two equally important components for the successful application of machine learning: a good algorithm, and a comprehensive set of training examples that span as much of the system-of-interest parameter space as possible.

In this course, students learn about machine learning and the data preparation workflow. The course begins with a portfolio of case studies to provide an overview of what can be accomplished with machine learning. Then, the fundamental machine learning tasks and algorithms are covered. The machine learning tasks and algorithms covered include multivariate nonlinear non-parametric regression, supervised classification, unsupervised classification, and deep learning. For these machine learning tasks, it is shown how to assess the quality of the machine learning models and perform error estimation and feature engineering.

You will learn:
  • Articulate the basic concepts and functioning of machine learning as well as its deployment in the business context
  • Broad introduction to machine learning, data mining, and statistical pattern recognition
  • Machine learning tasks and algorithms covered include multivariate nonlinear non-parametric regression, supervised classification, unsupervised classification, and deep learning
  • Best practices in machine learning
  • Applying Machine Learning
This course is geared towards:
  • Chief Data Officers
  • Chief Analytics Officers
  • VPs, Directors, and Managers of Data and Analytics
  • Data Engineers
  • Data Architects
  • Programmers
  • And anyone else interested in learning how to apply machine learning in business applications

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Courses
Courses > Data Science
Instructors
Instructors > Asha Saxena