Conv Nets IV

In this project, I extend my CNN Advanced Architecture project to 3D images. The architecture is advanced in the sense that it is flexible and can read & build its architecture from JSON files. The 3D extension allows CNN3D classifier to tackle 3D tensors used heavily in scientific/medical imaging such as CT Scan images, which we will we working with in this repo. I have trained the LUNA16 dataset with the usual my CNN and then with CNN3D classes and noted that CNN3D outperfromed the predictions for...

Brachistochrone

Light is one of the most amazing phenomena in the Universe. It is pure energy and has zero mass. If you could experience a moment as a photon, you would experience eternity in that moment, for light experiences no time of its own (technically you’d experience nothing as psychological experience is time dependent, but lets keep the poetic tone). It is one of the primordial constituents of the Universe and is considered sacred in all religions, ditto physics. Among other things, a path of light is Brachistochrone....

Result: Starry NIght Over Rhone, Neural Style Transfer

Alla Prima

Last month I watched Loving Vincent. The movie was a story of Van Gogh post Saint Rémy, in his final year in Auvers-sur-Oise. The story reconstructed the lonely artist’s mental breakdown from the perspectives of people close to him, well at least they are there in his paintings. Aside from reconstruction in a sense of narrative, the movie was also reconstruction in material. The entire movie comprised of animations of reimagined Van Gogh’s paintings. It recreated 94 Van Gogh’s originals while creating about 67K oil paintings around...

Conv Nets II

In this project we automate learning CNN hyper-params. We test and improve my previous tensorflow implementation of CNN in here on Kaggle's facial expression dataset. Here I only deal with two label classes: Happy and Angry. Randomized Search for learning hyper_paramters such as learning_rate, momentum coefficient, etc and drop-out regularizer improved the default test prediction accuracy from 36% to 64%. This is a bit lower than 72% that we got from our SVM classifier. However, we will continue in following projects to see if we can beat...

Conv Nets I

This project implements CNN class using the tensorflow library. I compare the accuracies gained by the ConvPool layers to the ANN architectures of the ANN-tensorflow repo. We find that adding only 2 ConvPool layers before the ANN architecture does automated feature engineering and significantly increases the classification accuracies as compared to the ANN only architectures....

Hypothesis Testing III – Bayesian Methods

This project is third in the series of Hypothesis testing project whereby we use Bayesian Methods. Here we reformulate the AB testing problem into MultiArm Bandit and implement 4 widely used algorithms: Epsilon Greedy, Optimistic Initial Conditions, UCB1, and Bayesian (Thompson) Sampling for the AB testing. We then compare and contrast the performance of the algorithms wrt the Bandit problem....