Sometimes it fails because the user does not know the concept he has to draw, or he/she is not able to complete it on time or just because the AI has not generalized well. While the player is drawing, the AI tries to guess what is being drawn.

The basic idea of the game is that it tells the player a simple concept (such as banana, apple…) and he/she has to draw it in a certain amount of time. Quick, Draw! is a game that was created in 2016 to educate the public in a playful way about how AI works. The idea and the dataset of our project is extracted from Quick, Draw! Doodle Recognition Challenge. Quick, Draw! Doodle Recognition Challenge Having said that, the technical goal of our project is to implement from scratch three different Deep Learning architectures of increasing difficulty (Multilayer Perceptron, Convolutional Neural Network and Long-Short Term Memory) that tackled in a different way a classification problem extracted from an ongoing Kaggle competition, and create for each model a self-contained and detailed Notebook that alternates text with code. Towards this goal, we have resolved a classification task that has allowed us to comprehend and perform all the steps of the pipeline of a Deep Learning project. We conceived this project as a way to deeply understand the concepts and implementations of various Deep Learning models studied in the course, for the majority of us are new to this fascinating world of Deep Learning.

Deep Learning for Artificial Intelligence Project | 2018-dlai-team10 2018-dlai-team10 View on GitHub Deep Learning for Artificial Intelligence Project

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