Summary Statistics as Features - Data Processing and Feature Engineering with MATLAB
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Summary Statistics as Features - Data Processing and Feature Engineering with MATLAB
Practical Data Science with MATLAB Specialization
In this course, you will build on the skills learned in Exploratory Data Analysis with MATLAB to lay the foundation required for predictive modeling. This intermediate-level course is useful to anyone who needs to combine data from multiple sources or times and has an interest in modeling.
These skills are valuable for those who have domain knowledge and some exposure to computational tools, but no programming background. To be successful in this course, you should have some background in basic statistics (histograms, averages, standard deviation, curve fitting, interpolation) and have completed Exploratory Data Analysis with MATLAB.
Throughout the course, you will merge data from different data sets and handle common scenarios, such as missing data. In the last module of the course, you will explore special techniques for handling textual, audio, and image data, which are common in data science and more advanced modeling. By the end of this course, you will learn how to visualize your data, clean it up and arrange it for analysis, and identify the qualities necessary to answer your questions. You will be able to visualize the distribution of your data and use visual inspection to address artifacts that affect accurate modeling.
Feature Engineering, Matlab, Data Cleansing
Great lectures! Great visuals, sounds, explanations are crystal clear, concise and yet in depth. It's a well paced course with very attentive instructors. Really enjoyed taking it!,The course is good and very well structured. It helps you understand the steps involved in feature engineering and provides proper ways to implement them in MATLAB.
In this module you'll apply the concepts from Modules 1 through 4 to different domains. You'll create and evaluate features using time-based signals such as accelerometer data from a cell phone. You'll use Apps in MATLAB to perform image processing and create features based on segmented images. You'll also use text processing techniques to find features in unstructured text.
Summary Statistics as Features - Data Processing and Feature Engineering with MATLAB
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