From the course: Deep Learning and Computer Vision: Object Detection with PyTorch
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Understanding neural networks - PyTorch Tutorial
From the course: Deep Learning and Computer Vision: Object Detection with PyTorch
Understanding neural networks
- [Instructor] Welcome back. In the last video, we saw how neural networks learn using the process of back propagation and grading descent. Now it's time to put that knowledge into action. In this video, we'll build and train a basic neural network to solve a simple task, and by the end, we'll be able to apply these concepts in the upcoming projects. We'll be building a simple field forward neural network through which data flows in one direction. That is from the input layer to the output layer. The architecture of this network includes an input layer, which takes in the input data, a hidden layer. Where is the intermediate neurons perform calculation and output layer, which gives us the final prediction for this task. Let's keep it simple. Let's use one input layer, one hidden layer, and one output layer. The number of neurons in each layer depends on the task we would be solving. But for now, we'll use two neurons in the input layer, three in the hidden layer, and one in the input…
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