Neural Network From Scratch - Mean Squared Error

Source Code : https://github.com/Guraku-Black/typelibrary/
#shorts

The Mean Squared Error is the difference between two arrays. Take the squared sum of the difference between each item in the two arrays. The goal of every neural neural network is to get that sum as close as possible to zero.

Using only the C Programming language and Visual Studio, We are going create a Neural Network that includes, Convolutional Layers, RELU, SIGMOID and TANH Layers, Fully Connected Layers, as well as Dropout Layers.

The basic problem with using programs like TensorFlow or Keras or even the Python language is that they hide a lot of the details of actually running a neural network. It can be hard for example to even find out anything about backpropagation in a Convolutional layer. If you want to really understand what is actually going on in Machine Learning Algorithms, Deep Learning, Computer Vision and Natural Language Processing, or Recurrent Neural Networks, you need to actually know the actual details of the code and not just rely on tools that do most of the work for you.

Видео Neural Network From Scratch - Mean Squared Error канала guraku