Artificial Neural Networks tutorial - theory & applications

About this course

This course aims to simplify concepts of Artificial Neural Network (ANN). ANN mimics the process of thinking. Using it's inherent structure, ANN can solve multitude of problem like binary classifications problem, multi level classification problem etc. The course is unique in terms of simplicity and it's step by step approach of presenting the concepts and application of neural network. The course has two section ------------------------------------------------------- Section 1 : Theory of artificial neural network -------------------------------------------------------- what is neural networkTerms associated with neural networkWhat is nodeWhat is bias What is hidden layer / input layer / output layer What is activation function What is a feed forward modelHow does a Neural Network algorithm work?What is case / batch updatingWhat is weight and bias updation Intuitive understanding of functioning of neural network Stopping criteria What decisions an analyst need to take to optimize the neural network?Data Pre processing required to apply ANN ------------------------------------------------------- Section 2 : Application of artificial neural network -------------------------------------------------------- Application of ANN for binary outcomeApplication of ANN for multi level outcomeAssignment of ANN - learn by doing

Course objectives

• simplify the concepts of ANN
• provide a thorough understanding of how ANN algorithms work
• enable practical application of ANN through hands-on assignments