A New Life

Week 1: Using CNN's with the Cats vs Dogs Dataset Welcome to the 1st assignment of the course! This week, you will be using the famous Cats vs Dogs dataset to train a model that can classify images of dogs from images of cats. For this, you will create your own Convolutional Neural Network in Tensorflow and leverage Keras' image preprocessing utilities. You will also create some helper functions..

Week 4: Handling Complex Images - Happy or Sad Dataset In this assignment you will be using the happy or sad dataset, which contains 80 images of emoji-like faces, 40 happy and 40 sad. Create a convolutional neural network that trains to 99.9% accuracy on these images, which cancels training upon hitting this training accuracy threshold. import matplotlib.pyplot as plt import tensorflow as tf im..

Week 3: Improve MNIST with Convolutions In the videos you looked at how you would improve Fashion MNIST using Convolutions. For this exercise see if you can improve MNIST to 99.5% accuracy or more by adding only a single convolutional layer and a single MaxPooling 2D layer to the model from the assignment of the previous week. You should stop training once the accuracy goes above this amount. It..

Week 2: Implementing Callbacks in TensorFlow using the MNIST Dataset In the course you learned how to do classification using Fashion MNIST, a data set containing items of clothing. There's another, similar dataset called MNIST which has items of handwriting -- the digits 0 through 9. Write an MNIST classifier that trains to 99% accuracy and stops once this threshold is achieved. In the lecture ..

Week 1 Assignment: Housing Prices In this exercise you'll try to build a neural network that predicts the price of a house according to a simple formula. Imagine that house pricing is as easy as: A house has a base cost of 50k, and every additional bedroom adds a cost of 50k. This will make a 1 bedroom house cost 100k, a 2 bedroom house cost 150k etc. How would you create a neural network that l..