Deep learning models have shown amazing performance in a lot of fields such as autonomous driving, manufacturing, and medicine, to name a few. However, these are fields in which representing model uncertainty is of crucial importance. Read more

In the last post, I introduced the U-Net model for segmenting salt depots in seismic images. This time, we will see how to improve the model by data augmentation and especially test time augmentation (TTA). You will learn how to use data augmentation with segmentation masks and what test time augmentation is and how to use it in keras. Read more

Today I’m going to write about a kaggle competition I started working on recently. In the TGS Salt Identification Challenge, you are asked to segment salt deposits beneath the Earth’s surface. So we are given a set of seismic images that are $101 \times 101$ pixels each and each pixel is classified as either salt or sediment. Read more

This time I will show you how to build a simple “AI” product with transfer learning. We will build a “dog breed identification chat bot”. In this first post, I will show how to build a good model using keras, augmentation, pre-trained models for transfer learning and fine-tuning. Read more

In this article, we will apply the concept of multi-label multi-class classification with neural networks from the last post, to classify movie posters by genre. First we import the usual suspects in python. import numpy as np import pandas as pd import glob import scipy. Read more