The science of Machine Learning / Artificial Intelligence (broadly speaking) is a complex one. It lies at the heart of numerous intersecting fields like Mathematics, Computer Science, Electrical and Electronics Engineering, Statistics, Neuroscience, Pschology etc. To master these concepts and apply them to the real world is not that easy at it seems. Most of the practitioners today complete a set of online courses and claim themselves to be AI experts. It takes time, effort and most importantly intuition and strong fundamental concepts of Mathematics and Statistics to understand the underlying data and techniques to model them. My active areas of research and study have been in the following areas : Adversarial Training - Generative Adversarial Networks applied to the fields of Computer Vision and Voice generation. I have explored the SEGAN, CycleGAN, DiscoGAN, StarGAN, AutoencoderGAN, DCGAN etc Machine learning system design (End - End) I am here to help you. Send me a brief message explaining your problem and I shall get back to you as soon as possible.