Deep Learning - Python
Developed RNN and CNN models.
In this Deep Learning project I work with Convolutional Neural Networks, Recurrent Neural Networks, and Natural Language Programming.
I worked with Tensorflow and Keras mainly, using Python, to predict housing prices with a RNN model. I also created a CNN model to clasify images in a dataset composed of 60,000 pictures.
Results
+2
Deep Learning Models:
RNN and CNN
+2
Feature Engineering and Tuning
95%
Grade on Deep Learning Class
Goals
The objective of the project is to make multiple Deep Learning models, in different ways, to solve the problems given by our professor for Deep Learning class. These problems include, predicting household prices in Boston with 13 input variables, classifying 10 types of objects in a set of 60,000 images, and predict in a third model minimum temperatures in Melbourne, Australia.