British Columbia wildfires are burning out of control! There were a number of air quality warnings issued cross BC in summer 2018. Smoky air flew all the way to Alberta and even cross the border to US. It made me curious what’s going on with BC wildfires and what the situation was used to be.
Wildwire datasets for previous years and current year (updated in May 2018) were gathered from DataBC, data published by BC Wildfire Service. For relevance and clarity, data prior to 1980 is ignored.
Key learning elements:
» Run experiments in Google Colab and access files on Google Drive
» Build and evaluate a model using Tensorflow Eager mode
» Build a Convolutional Neural Network (CNN) to recognize 7 facial expressions
For this exercise we are going to build a CNN for facial expression recognition on fer2013 dataset, available on Kaggle. fer2013 is a publicly accessible, and it contains 35,887 grayscale, 48 x 48 sized face images with 7 emotional expressions: angry, disgust, fear, happy, sad, surprise, and neutral. It was originally published on International Conference on Machine Learning (ICML) 2013, Challenges in Representation Learning: A report on three machine learning contests, Ian Goodfellow et al., 2013
Continue reading “Build CNN for facial expression recognition with TensorFlow Eager on Google Colab”
