In this chapter, we saw how to develop a neural network model that helps to solve a classification type of problem. We started with a simple classification model and explored how to change the number of hidden layers and the number of units in the hidden layers. The idea behind exploring and fine-tuning a classification model was to illustrate how to explore and improve the performance of the classification model. We also saw how to dig deeper to understand the performance of a classification model with the help of a confusion matrix. We purposefully looked at a relatively smaller neural network model at the beginning of this chapter and finished with an example of a relatively deeper neural network model. Deeper networks involving several hidden layers can also lead to overfitting problems, where a classification model may have excellent performance with training data...
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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