In this chapter, we went through the steps for developing a prediction model when the response variable is of a numeric type. We started with a neural network model that had 201 parameters and then developed deep neural network models with over 7,000 parameters. You may have noticed that, in this chapter, we made use of comparatively deeper and more complex neural network models compared to the previous chapter, where we developed a classification model for the target variable that was of a categorical nature. In both Chapter 2, Deep Neural Networks for Multiclass Classification, and Chapter 3, Deep Neural Networks for Regression, we developed models based on data that was structured. In the next chapter, we move on to problems where the data type is unstructured. More specifically, we'll deal with the image type of data and go over the problem of image classification...
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Bharatendra Rai is a chairperson and professor of business analytics, and the director of the Master of Science in Technology Management program at the Charlton College of Business at UMass Dartmouth. He received a Ph.D. in industrial engineering from Wayne State University, Detroit. He received a master's in quality, reliability, and OR from Indian Statistical Institute, India. His current research interests include machine learning and deep learning applications. His deep learning lecture videos on YouTube are watched in over 198 countries. He has over 20 years of consulting and training experience in industries such as software, automotive, electronics, food, chemicals, and so on, in the areas of data science, machine learning, and supply chain management.
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Bharatendra Rai is a chairperson and professor of business analytics, and the director of the Master of Science in Technology Management program at the Charlton College of Business at UMass Dartmouth. He received a Ph.D. in industrial engineering from Wayne State University, Detroit. He received a master's in quality, reliability, and OR from Indian Statistical Institute, India. His current research interests include machine learning and deep learning applications. His deep learning lecture videos on YouTube are watched in over 198 countries. He has over 20 years of consulting and training experience in industries such as software, automotive, electronics, food, chemicals, and so on, in the areas of data science, machine learning, and supply chain management.
Read more about Bharatendra Rai