Ai for Business

(This article is a reproduction of the lectures I have given in Engineering Colleges in Mumbai, for students and faculty) In a previous article, I have suggested the DTOP (Data-Technology-Objective-Possibilities) framework (see https://www.linkedin.com/pulse/4-hints-get-started-ai-your-company-devesh-rajadhyax)to analyse AI use cases in a company. Today I am going to use the same framework to explain some applications of AI to Computational Biology(CB). In this article I will focus more on the data aspect. There is a reason. Biological data is probably the most important kind data for us. However, very few engineers have a good understanding of this data. I will be very happy if this article encourages some engineers to study biological data in detail. Understanding and experience with this data will become a much wanted skill in near future. Let me first put CB use cases in DTOP.   Data : Biological data is of many types. I will mention three major types here and explain one ...

  Most companies are working on Digital Transformation today, and Artificial Intelligence is a critical part of that transformation. Two questions immediately present themselves- 1.    What is Digital Transformation and how it is different from the IT/ICT transformation that is happening since for than four decades? 2.    Why is AI a critical part of this transformation? Let me take the first question. Digital Transformation is actually a cognitive revolution. It is a more humanlike way of making sense of the world around. And this is our clue to the most important difference between IT and Digital- ‘IT systems are not humanlike. They don’t try to make sense of the world around them. They create a small world of their own and everyone follows the rules of that world. The input has to be given in the way they demand and output will be available in forms that they prefer. You better fall in line. Digital, or Cognitive systems would want to fit ...

  Artificial Intelligence is receiving more than its fair share of public attention. On one side there are promises of miracles, while on the other side there are warnings of doomsday. What is probably missing is a simple listing of clear benefits. This is article is an attempt to create such a list. Artificial Intelligence is more of an ambition than a technology. The ambition is to imitate human capabilities. Since human capabilities range from walking to solving mathematical problems, AI also encompasses systems of various types – ranging from the humble calculator to Google’s DeepMind. In this article, I am majorly referring to the AI systems that try to achieve the cognitive abilities of human beings. Cognitive abilities refer to the processes of our mind such as understanding, reasoning, planning and selecting the right action. Understanding a question and supplying the right answer from our memory is an example of cognitive ability, the one that AI systems called ‘chatbots’ ...

  Understanding Projection Pursuit Regression The following article gives an overview of the paper "Projection Pursuit Regression” published by Friedman J. H and Stuetzle W. You will need basic background of Machine Learning and Regression before understanding this article. The algorithms and images are taken from the paper. ( http://www.stat.washington.edu/courses/stat527/s13/readings/FriedmanStuetzle_JASA_1981.pdf )  What is Regression? Regression is a machine learning technology used to predict a response variable given multiple predictor variables or features. The main distinction is that the response to be predicted is any real value and not just any class or cluster name. Hence though similar to Classification in terms of making a prediction, it is largely different given what it’s predicting.  A simple to understand real world problem of regression would be predicting the sale price of a particular house based on it’s square footage, given that we have da...