- ๐ Computer Science and Business Double Degree (CS/BBA) student at University of Waterloo
- ๐ฌ Ask me about cricket ๐ , swimming ๐ , Traveling
โ๏ธ , or Ping Pong ๐ via my website - ๐ต Let me know if you like Drake , The Weeknd, or Post Malone and maybe we could give each other music recommendations
- ๐ I'm currently working on a project called Fooder that's meant for users having difficulty choosing what to eat. It allows users to swipe through dishes (based off nearby restaurants and dietary restrictions, etc.) and match them with a restaurant
ynoza / traffic Goto Github PK
View Code? Open in Web Editor NEWThis project creates a model using neural network layers that can predict which street sign is which. To do this, the project took use of the German Traffic Sign Recognition Benchmark, which contains a huge data base of 43 common street signs. This data was then organized into numpy arrays, and then placed into training and testing sets. A neural network model was then created using many hidden layers (i.e convolutional and average pooling) to train the model on our data set. The model was then finally evaluated and an accuracy percentage of about 97.5% was recorded. Huge credits go to Harvard's CS_50 course, in particular the introduciton to artificial intelligence with python portion of the course. This repository is a project that was assigned to me from this course, so CS_50 has ownership to portions of the source code.