Deep learning fundamentals – logistic regressions

12 Feb 2017 This blog captures an intuitive understanding of concepts such as Regression analysis required for deeplearning. The following are summary of my notes from week 1 of the Udacity Deep Learning course. Linear regression is used to model the relationship between a dependent variable and an independent variable. The intent is to draw a line through your data that best fits your data. … Continue reading Deep learning fundamentals – logistic regressions

Teach a program to paint like Van Gogh

02 Feb 2017 There are some things that completely blow your mind. Applying artist specific styles to images is one of them. Completely sci-fiction – although the Prisma filter has made this accessible. In the last blog, I set up the core software requirements for the Udacity deeplearning course. This blog uses the setup to transfer the styles of 3 famous paintings and apply it to images. … Continue reading Teach a program to paint like Van Gogh

Setting up Anaconda for deep learning

28 Jan 2017  //embedr.flickr.com/assets/client-code.js This blog sets up the core software requirements for the Udacity deeplearning course to get you started quickly. I have just signed up for the deeplearning course and am fairly excited about it. The course heavily depends on Python – I used Python about 18 years back and have been a java guy since. The course requires you to setup Python 3.5, a … Continue reading Setting up Anaconda for deep learning