I will be teaching an introductory course in machine learning for students in management who have minimal quantitative skills. I am looking for a brief and gentle introduction to neural networks that I could cover in a 90-minute lecture. I would like to mention the basic principles of the mechanics of NNs as well as give a brief overview of their potential use. Such a lecture could be based on one chapter of a book. I was hoping to find a good exposition in James et al. "Introduction to Statistical Learning" on which I am basing some of the other lectures, but the topic is not covered there. I have consider the relevant chapter in Friedman et al. "Elements of Statistical Learning" but did not find it satisfactory. Kuhn & Johnson "Applied Predictive Modeling" has a section on NNs, but it is a little too brief.
In addition, I would also like to give a brief and inevitably superficial overview of the more advanced versions of neural networks that are in use today. This is probably getting too broad, but I will appreciate any tips.
