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Predicting Traffic Signs using Neural Networks (Deep Learning with TensorFlow)

Introduction

Deep learning is a field from machine learning that uses algorithms inspired by how neurons function in the human brain. TensorFlow is a machine learning framework that Google created to design, build, and train deep learning models. The name, "TensorFlow", is derived from how neural networks perform on multidimensional data arrays or tensors. It's a flow or tensors, just like how the human brain has a flow of neurons! Our tool that we will be using today is TensorFlow!

Conclusion

Our Neural Network got an accuracy score of 68.3%. Considering that this project didn't fully utilize a GPU or an extensive neural network, I would say that this is pretty good.

Some improvements that could be made could be applying LDA before feeding to our model, early or late stopping of training, and tuning our optimizers. With extensive improvements to this starter, we could re-use this and apply it to self-driving cars or other autonomous vehicles in the future!

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Predicting Traffic Signs using Neural Networks (Deep Learning with TensorFlow)

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