Data Science, Machine Learning and more..

     This chapter is the first chapter of the part - 1. This part prepares you for Deep learning and in this chapter Linear Algebra is covered. The author advice you to skip the chapter if you are already familiar with the concepts. Also it is not that you can become Gilbert Strang after reading this chapter! The chapter is so concise that what may be relevant to our future acquaintance with the book are only present here. Only at the end of the chapter some concepts author speaks on the application part. The focus is on mathematical concepts involving Linear Algebra.       Though Science and Engineering use Linear Algebra efficiently, Computer scientist have lesser experience with it. This is the motivation of the chapter and if you have experience it then author provides you with a reference (The Matrix Cookbook - Petersen and Pedersen, 2006) and waves you good bye to meet in the next chapter.      Definitions ...

Chapter 1 - Introduction       This is the introductory chapter to the book. Here the authors introduce deep learning, advises what the book is actually about and finally gives the path that deep learning  has traveled to make it to the current state. Introduction to Deep Learning...     They are clearly giving the picture that it is a book for intermediate. The motivation for data, the hype of Artificial intelligence and the societal impacts, which are typical of an introductory chapter of an introductory book is cut down to a very minimal level here. The book says that Artificial intelligence has solved many problems that are beyond human ability but the actual challenge of AI is solving the intuitive problems which humans do in their day to day life. And that the concentration of the book will be on solving these kinds of problem.     Deep learning is introduced as hierarchy of concepts, where complicated conc...

    I bought a Deep Learning textbook this week! Deep Learning by Ian Goodfellow, Yoshua Bengio and Aaron Courville.     I bought it after a very thorough research on the contents and previous reviews. And actually it is a good choice. This book has developed to be one of the fundamental textbooks of Deep learning and is the latest of them.        I am excited about the book when i started reading it. But i feel reading is very lonely, i want to say what is actually exciting. I want to help some one who wants to know what the book is about. So i thought of writing a chapter wise review of the book. I plan to release review of each chapter on Fridays starting today(31/01/2019). I will keep updating this post with the links to the review of the chapter. This is my first experience in technical book review and i am hoping to do my best.   Chapter No Name Link Published/Scheduled Date 1 Introduction https:...