

TechSource Systems is MathWorks Authorised Reseller and Training Partner
Learn to create regression, classification, and clustering models and improve performance for data analytics
This two-day course focuses on data analytics and machine learning techniques in MATLAB® using functionality within Statistics and Machine Learning Toolbox™ and Deep Learning Toolbox™. The course demonstrates the use of unsupervised learning to discover features in large data sets and supervised learning to build predictive models. Examples and exercises highlight techniques for visualization and evaluation of results. Topics include:
This course is intended for engineer, researchers, data scientists, and managers, who are involved in the design of intelligent systems that can automatically produce models which can analyse bigger, more complex data and deliver faster and more accurate results.
MATLAB Fundamentals
Upon the completion of the course, the participants will be able to:
TechSource Systems is MathWorks Authorised Reseller and Training Partner
Objective: Bring data into MATLAB and organize it for analysis, including normalizing data and removing observations with missing values.
Objective: Use unsupervised learning techniques to group observations based on a set of explanatory variables and discover natural patterns in a data set.
Objective: Use supervised learning techniques to perform predictive modeling for classification problems. Evaluate the accuracy of a predictive model.
Objective: Reduce the dimensionality of a data set. Improve and simplify machine learning models.
Objective: Use supervised learning techniques to perform predictive modeling for continuous response variables.
Objective: Create and train neural networks for clustering and predictive modeling. Adjust network architecture to improve performance.